Comparison of the diagnostic yield of rapid versus non-rapid onsite evaluation in endoscopic ultrasound-guided fine-needle aspiration cytology of solid pancreatic lesions.

Background: The role of rapid on-site evaluation (ROSE) for endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) of pancreatic lesions is debatable. In this study, we aimed to compare the diagnostic yield of ROSE vs. non-ROSE in solid pancreatic lesions. Methods: This retrospective single-center study included patients undergoing EUS-FNA of solid pancreatic lesions from 2019-2021. Patients with cystic lesions, those undergoing fine-needle core biopsy, those undergoing repeat procedures, and patients with non-diagnostic smears with less than 6-month follow up were excluded. The diagnostic yield, need for repeat procedures and number of passes required with and without ROSE were analyzed in these patients. Results: Of the 111 patients included, 56 underwent ROSE. The majority of lesions were malignant in both groups (79.6% ROSE vs. 75% non-ROSE). The diagnostic yield was 96.4% in the ROSE group and 94.5% in the non-ROSE group. Repeat samples were needed in 1 ROSE and 2 non-ROSE patients. The median number of passes made was significantly fewer in the ROSE group (3.5, interquartile range - 3,4) compared with the non-ROSE group (4, interquartile range - 3,5) P=0.01. However, the frequency of procedure-related complications was similar in both groups. Conclusion: The utilization of ROSE during EUS-FNA of solid pancreatic lesions does not affect the diagnostic yield or the need for repeat samples, but reduces the number of passes needed for acquiring samples.

Bile Culture May Guide Antibiotic Stewardship in Acute Bacterial Cholangitis.

BACKGROUND: Bile cultures are often sent with blood cultures in patients with acute bacterial cholangitis. AIMS: To assess the yield of blood and bile cultures in patients with cholangitis and the clinical utility of bile cultures in guiding therapy. METHODS: All patients diagnosed with cholangitis, based on the Tokyo 2013/2018 guidelines were recruited retrospectively over ten years. The clinical and investigation details were recorded. The results of bile and blood cultures including antibiotic sensitivity patterns were noted. The concordance of microorganisms grown in blood and bile cultures and their sensitivity pattern were assessed. RESULTS: A total of 1063 patients with cholangitis were included. Their mean age was 52.7 ± 14 years and 65.4% were males. Blood cultures were positive in 372 (35%) patients. Bile culture was performed in 384 patients with 84.4% being positive, which was significantly higher than the yield of blood culture (p < 0.001). Polymicrobial growth was more in bile (59.3%) than in blood cultures (13.5%, p < 0.001). E.coli, Klebsiella, Enterococcus and Pseudomonas were the four most common organisms isolated from both blood and bile. Extended spectrum betalactamase producing organisms were isolated in 57.7% and 58.8% of positive blood and bile cultures, respectively. Among 127 patients with both blood and bile cultures positive, complete or partial concordance of organisms was noted in about 90%. CONCLUSION: Bile and blood cultures have a similar microbial profile in most patients with cholangitis. As bile cultures have a significantly higher yield than blood cultures, they could effectively guide antimicrobial therapy, especially in those with negative blood cultures.

Clinical profile of 1208 newly diagnosed colorectal cancer patients in Tamil Nadu-A multi-centric survey.

BACKGROUND: An increasing incidence of colorectal cancer (CRC) is being reported in developing countries, including India. Most Indian studies on CRC are retrospective and single-centered. The present study is an attempt to understand the current clinical profile and stage of newly diagnosed CRCs across multiple centers in Tamil Nadu, India. METHODS: A multi-centric observational survey was conducted between September 1, 2021, and August 31, 2022, under the aegis of the Indian Society of Gastroenterology - Tamil Nadu chapter. Patients 18 years of age and older with a recent diagnosis of CRC fulfilling the inclusion criteria were prospectively recruited at the participating centers. Their demographic, clinical, biochemical, endoscopic, histopathologic, radiologic and risk factor details were systematically collected and analyzed. RESULTS: Across 23 centers in Tamil Nadu, 1208 patients were recruited. The male:female ratio was 1.49:1, while mean (SD) age was 57.7 (13.5) years. A majority (81.9%) were Tamils and 78.5% belonged to lower socioeconomic classes. The predominant symptoms were hematochezia (30.2%) and a change in bowel habits (27.5%). The most common locations were the rectum (34.3%) and rectosigmoid (15.1%). Synchronous CRCs were seen in 3.3% and synchronous colorectal polyps in 12.8%. Predisposing factors for CRC were seen in 2%. A past history of any cancer among CRC patients was obtained in 3.1% and a family history of any cancer was found in 7.6%. Patients who were either overweight or obese constituted 46.4% of the study population. At presentation, the predominant stages were stage III (44.7%) and stage IV (20.8%). CONCLUSIONS: A majority of patients with newly diagnosed CRC in Tamil Nadu belonged to the lower socioeconomic classes. About 60% had CRCs located within the reach of the flexible sigmoidoscope. Two-thirds of the patients exceeded stage II disease at presentation. TRIAL REGISTRATION: Not applicable.

Central nervous system manifestations of dengue infection: data from a tertiary care Centre in South India.

BACKGROUND: Dengue fever is the second most common mosquito-borne disease affecting human beings and neurological manifestations (NMs) of this arboviral infection are increasingly being reported. METHODS: In this retrospective study, conducted in a tertiary care centre in south India, we sought to describe the spectrum of NMs of dengue fever. The records of all patients admitted in the Department of Internal Medicine over 8 years, with a diagnosis of dengue-based on clinical symptoms and the detection of dengue IgM antibodies or detection of NS1 antigen or nucleic acid by reverse transcriptase-polymerase chain reaction (RT-PCR); with Glasgow coma score (GCS) ≤14, neck stiffness, focal neurological signs, seizures, or visual disturbances-were explored. RESULTS: Of 1121 patients admitted with dengue fever, 341 (30%) had severe dengue and 23 (2%) had NMs. Encephalopathy was seen in 9 patients (39%), encephalitis in 6 (27%), cerebellitis in 4 (17%), acute disseminated encephalomyelitis (ADEM) in 2 (9%), ischaemic stroke in 1 (4%) patient, and neuro-ophthalmological manifestations in 1 (4%) patient. The median duration of hospital stay was 7 days. Nine (39% of) patients required intensive care unit (ICU) admission and 5 (22%) had fatal outcomes. There was no association between thrombocytopenia, metabolic acidosis, transaminitis, hyponatremia, the type of dengue infection, and the various NMs described. CONCLUSIONS: The NMs of dengue infection are varied, and a high index of suspicion is needed to identify them in patients who present with lethargy or altered sensorium on the background of an acute febrile illness suggestive of dengue.

Pulmonary tuberculosis and diabetes mellitus: Clinical profile and outcomes.

Background: India is endemic for Tuberculosis (TB), contributing to the world's highest number of active cases. Diabetes (DM), with its increasing burden in India, could contribute to adverse outcomes among patients with TB. Methods: Consecutive patients with sputum smear positive pulmonary tuberculosis were included in the study. We defined cases as those patients with diabetes at recruitment. Controls were non diabetics (NDM). Sputum samples for AFB smears, AFB culture and Xpert PCR along with blood samples for glycosylated Haemoglobin and glucose levels were collected at recruitment and at 6 months from patients with sputum positive pulmonary TB. Blood glucose levels and sputum smears were repeated at 2 months and monthly till they tested negative. The primary outcome studied was mortality at 6 month follow-up. The secondary outcomes included the time to conversion of sputum smears and cure rates between cases and controls. Results: We recruited 124 patients of which 68 were cases. Mortality after therapy was 15% in cases and 7% in controls, however, the difference was not statistically significant. Equal proportions in each group (Diabetics: 9% vs. NDM 9%) had persistent smear positivity at 2 months. There was no association between delayed sputum conversion and uncontrolled diabetes. Only about 57% of cases and 50% of controls were documented to have completed treatment or been cured. A significant reduction in HbA1c after 6 months of Antituberculous therapy was noted among the cases. [Mean difference - 1.76, P-value - 0.001, 95% CI of difference - (1.01 - 2.52)]. Conclusions: Diabetes did not have adverse outcomes in the form of increased mortality or delayed sputum conversion rates. The high proportion of loss to follow-up seems to be a trend of concern, which should be addressed emergently.

Automated identification of innocent Still's murmur using a convolutional neural network.

Background: Still's murmur is the most prevalent innocent heart murmur of childhood. Auscultation is the primary clinical tool to identify this murmur as innocent. Whereas pediatric cardiologists routinely perform this task, primary care providers are less successful in distinguishing Still's murmur from the murmurs of true heart disease. This results in a large number of children with a Still's murmur being referred to pediatric cardiologists. Objectives: To develop a computer algorithm that can aid primary care providers to identify the innocent Still's murmur at the point of care, to substantially decrease over-referral. Methods: The study included Still's murmurs, pathological murmurs, other innocent murmurs, and normal (i.e., non-murmur) heart sounds of 1,473 pediatric patients recorded using a commercial electronic stethoscope. The recordings with accompanying clinical diagnoses provided by a pediatric cardiologist were used to train and test the convolutional neural network-based algorithm. Results: A comparative analysis showed that the algorithm using only the murmur sounds recorded at the lower left sternal border achieved the highest accuracy. The developed algorithm identified Still's murmur with 90.0% sensitivity and 98.3% specificity for the default decision threshold. The area under the receiver operating characteristic curve was 0.943. Conclusions: Still's murmur can be identified with high accuracy with the algorithm we developed. Using this approach, the algorithm could help to reduce the rate of unnecessary pediatric cardiologist referrals and use of echocardiography for a common benign finding.

Benchmarking AutoML frameworks for disease prediction using medical claims.

OBJECTIVES: Ascertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets. MATERIALS AND METHODS: We generated a large dataset using historical de-identified administrative claims including demographic information and flags for disease codes in four different time windows prior to 2019. We then trained three AutoML tools on this dataset to predict six different disease outcomes in 2019 and evaluated model performances on several metrics. RESULTS: The AutoML tools showed improvement from the baseline random forest model but did not differ significantly from each other. All models recorded low area under the precision-recall curve and failed to predict true positives while keeping the true negative rate high. Model performance was not directly related to prevalence. We provide a specific use-case to illustrate how to select a threshold that gives the best balance between true and false positive rates, as this is an important consideration in medical applications. DISCUSSION: Healthcare datasets present several challenges for AutoML tools, including large sample size, high imbalance, and limitations in the available features. Improvements in scalability, combinations of imbalance-learning resampling and ensemble approaches, and curated feature selection are possible next steps to achieve better performance. CONCLUSION: Among the three explored, no AutoML tool consistently outperforms the rest in terms of predictive performance. The performances of the models in this study suggest that there may be room for improvement in handling medical claims data. Finally, selection of the optimal prediction threshold should be guided by the specific practical application.

Neuromorphic Architecture Accelerated Automated Seizure Detection in Multi-Channel Scalp EEG.

Epileptic focal seizures can be localized in the brain using tracer injections during or immediately after the incidence of a seizure. A real-time automated seizure detection system with minimal latency can help time the injection properly to find the seizure origin accurately. Reliable real-time seizure detection systems have not been clinically reported yet. We developed an anomaly detection-based automated seizure detection system, using scalp-electroencephalogram (EEG) data, which can be trained using a few seizure sessions, and implemented it on commercially available hardware with parallel, neuromorphic architecture-the NeuroStack. We extracted nonlinear, statistical, and discrete wavelet decomposition features, and we developed a graphical user interface and traditional feature selection methods to select the most discriminative features. We investigated Reduced Coulomb Energy (RCE) networks and K-Nearest Neighbors (k-NN) for its several advantages, such as fast learning no local minima problem. We obtained a maximum sensitivity of 91.14%±1.77% and a specificity of 98.77%±0.57% with 5 s epoch duration. The system's latency was 12 s, which is within most seizure event windows, which last for an average duration of 60 s. Our results showed that the CD feature consumes large computation resources and excluding it can reduce the latency to 3.6 s but at the cost of lower performance 80% sensitivity and 97% specificity. We demonstrated that the proposed methodology achieves a high specificity and an acceptable sensitivity within a short delay. Our results indicated also that individual-based RCE are superior to population-based RCE. The proposed RCE networks has been compared to SVM and ANN as a baseline for comparison as they are the most common machine learning seizure detection methods. SVM and ANN-based systems were trained on the same data as RCE and K-NN with features optimized specifically for them. RCE nets are superior to SVM and ANN. The proposed model also achieves comparable performance to the state-of-the-art deep learning techniques while not requiring a sizeable database, which is often expensive to build. These numbers indicate that the system is viable as a trigger mechanism for tracer injection.

A fatal case of levamisole induced bone marrow failure.

A 20-year-old college student presented with high grade, intermittent fever for 10 days associated with blood stained loose stools after taking tablet levamisole for 17 days for vitiligo vulgaris. He was febrile, had a toxic appearance and appeared pale. Investigations showed neutropaenia with thrombocytopaenia. Blood cultures were sterile and stool cultures did not grow any enteric pathogens. His bone marrow examination was suggestive of an aplastic anaemia. He was administered empirical antibiotics, granulocyte colony stimulating factor and platelet transfusions. However, his fever and blood stained stools persisted. A repeat bone marrow examination after 2 weeks still revealed a hypoplastic marrow. Hence, a diagnosis of a levamisole induced bone marrow failure was made. While being worked up for an allogeneic stem cell transplantation, he developed neutropaenic enterocolitis and refractory septic shock with carbapenem resistant Klebsiella pneumoniae and succumbed to his illness.

Visceral leishmaniasis with haemophagocytic lymphohistiocytosis.

A 27-year-old man presented with high-grade intermittent fever for 4 months, generalised fatigue for 2 months, intermittent gum bleeds for 1 month and loss of weight of 15 kg. He appeared cachectic with generalised wasting, had pallor and features of reticuloendothelial system proliferation. His liver span was 17 cm. He had massive splenomegaly. His cardiovascular, respiratory and neurological examination were normal. He was diagnosed to have visceral leishmaniasis (VL) based on bone marrow (BM) examination that showed Leishmania donovani (LD) bodies and was treated with liposomal amphotericin (LA). During the course of therapy, he developed bleeding from various mucosal and venepuncture sites. His further evaluation, which included a repeat BM aspirate, showed haemophagocytes. Final diagnosis made was VL with secondary haemophagocytic lymphohistiocytosis. He was continued on LA with intravenous hydrocortisone. He developed refractory distributive shock with multiorgan dysfunction and succumbed to his illness.

Correlation between the outcomes and severity of diabetic ketoacidosis: A retrospective pilot study.

INTRODUCTION: Diabetic ketoacidosis (DKA) is a serious acute metabolic complication of diabetes mellitus (DM). It is classified into mild, moderate, and severe based on severity as per the American Diabetes Association (ADA) guidelines. There are limited data on the correlation between the severity of DKA and its outcomes using this classification system. The aim is to study the correlation between the outcomes and severity of DKA in a tertiary care center in India. METHODOLOGY: In this retrospective pilot study, 1527 patients with DM were identified over a span of 3 years, of which 63 had a discharge diagnosis of DKA and 37 fulfilled the ADA criteria for DKA. Following inclusion details on clinical parameters and outcomes of patients with mild, moderate, and severe DKA were compared. RESULTS: Mild, moderate, and severe DKA accounted for 8%, 41%, and 51% of the patients, respectively. Intensive Care Unit (ICU) care was required in 6.7% and 47.4% of those with moderate and severe DKA, respectively. Invasive ventilation (IV) was required in 47% (9) of those with severe DKA only. The mortality rates were 13.3% and 26% among those with moderate and severe DKA. The mean expenditure was ₹29,000, ₹30,000, and ₹64,000 among those with mild, moderate, and severe DKA, respectively. CONCLUSIONS: The ADA classification of severity of DKA correlates well with the duration of inhospital stay, costs of care, requirement of ICU care, need for IV or non-IV, and mortality. This suggests that this classification system could be a valuable tool in predicting outcomes.

An automated rat single pellet reaching system with high-speed video capture.

BACKGROUND: Single pellet reaching is an established task for studying fine motor control in which rats reach for, grasp, and eat food pellets in a stereotyped sequence. Most incarnations of this task require constant attention, limiting the number of animals that can be tested and the number of trials per session. Automated versions allow more interventions in more animals, but must be robust and reproducible. NEW METHOD: Our system automatically delivers single reward pellets for rats to grasp with their forepaw. Reaches are detected using real-time computer vision, which triggers video acquisition from multiple angles using mirrors. This allows us to record high-speed (>300 frames per second) video, and trigger interventions (e.g., optogenetics) with high temporal precision. Individual video frames are triggered by digital pulses that can be synchronized with behavior, experimental interventions, or recording devices (e.g., electrophysiology). The system is housed within a soundproof chamber with integrated lighting and ventilation, allowing multiple skilled reaching systems in one room. RESULTS: We show that rats acquire the automated task similarly to manual versions, that the task is robust, and can be synchronized with optogenetic interventions. COMPARISON WITH EXISTING METHODS: Existing skilled reaching protocols require high levels of investigator involvement, or, if ad libitum, do not allow for integration of high-speed, synchronized data collection. CONCLUSION: This task will facilitate the study of motor learning and control by efficiently recording large numbers of skilled movements. It can be adapted for use with modern neurophysiology, which demands high temporal precision.

Genome Sequences of Three Phytopathogenic Species of the Magnaporthaceae Family of Fungi.

Magnaporthaceae is a family of ascomycetes that includes three fungi of great economic importance: Magnaporthe oryzae, Gaeumannomyces graminis var. tritici, and Magnaporthe poae. These three fungi cause widespread disease and loss in cereal and grass crops, including rice blast disease (M. oryzae), take-all disease in wheat and other grasses (G. graminis), and summer patch disease in turf grasses (M. poae). Here, we present the finished genome sequence for M. oryzae and draft sequences for M. poae and G. graminis var. tritici. We used multiple technologies to sequence and annotate the genomes of M. oryzae, M. poae, and G. graminis var. tritici. The M. oryzae genome is now finished to seven chromosomes whereas M. poae and G. graminis var. tritici are sequenced to 40.0× and 25.0× coverage respectively. Gene models were developed by the use of multiple computational techniques and further supported by RNAseq data. In addition, we performed preliminary analysis of genome architecture and repetitive element DNA.