Ceftraixone induced anaphylaxis and death: a case report

Ceftriaxone, a broad spectrum third generation cephalosporin antibiotic and sulbactam is a beta-lactamase inhibitor. The combination is used for pre-operative surgical prophylaxis for prevention is secondary bacterial infection.  We describe a patient who developed anaphylaxis and death soon after intravenous administration of ceftriaxone and sulbactam combination and review similar cases of adverse effects to these class of drugs. The patient was a 68 year old male admitted to surgery ward for obstructed inguinal hernia. He was prescribed injection ceftriaxone and sulbactam combination along with concomitant medication injection pantoprazole and injection metronidazole. The patient was injected injection ceftriaxone and sulbactam, within 15 minutes he suddenly developed anaphylactic shock and died for fluid aspiration in lungs during resuscitation. PubMed was searched for the following terms: anaphylaxis, ceftriaxone, sulbactam. The papers containing these terms and their references were reviewed. Anaphylactic shock caused by ceftriaxone is an uncommon adverse event in patients receiving the drug. However, similar reactions have been observed in some cases in India and world-wide. Clinicians should be aware that anaphylaxis secondary to ceftriaxone and sulbactam combination is a serious death threatening side-effect

Drug utilization study of bronchial asthma in adults at rural hospital

Background: Asthma is rather a clinical syndrome than a disease with availability wide range of medications. Drug utilization studies are necessary to improve prescribing pattern among physicians.Methods: The 250 study subjects were interviewed, and prescription data was recorded in a pre-designed case record form. The data was compiled using Microsoft excel and presented in a tabulated and graphical presentation.Results: Out of 250 study subjects most of the study subjects are between 61-70 years of age. Majority of subjects are males (58%). Out of 250, (49%) are found out to be smokers. Dust, smoke and pollen are found out to be most common allergen. Most common type of asthma was mild intermittent (134) study subjects. Socio-economic status of was found out to be lower middle class in majority (158 out of 250). Large number of study population is suffering from co-morbid conditions such as URTI and COPD. Salbutamol was most common single drug used for nebulization therapy and most common combination is salbutamol + ipatropium bromide + budesonide. Most common oral drug used are methylxanthines and most frequently used intravenous drugs are deriphylline and hydrocortisone. Various antibiotics are prescribed to majority of subjects, most common was amoxicillin + clavulanic acid combination. Most commonly suffered adverse drug reaction between study subjects were gastrointestinal disturbances.Conclusions: It is concluded that prescribing pattern for asthma at A.V.B.R.H. is not according to standard guidelines, hence it is need of the hour to encourage physicians to follow guidelines

Target heterogeneity in oncology : the best predictor for differential response to radioligand therapy in neuroendocrine tumors and prostate cancer

Tumor or target heterogeneity (TH) implies presence of variable cellular populations having different genomic characteristics within the same tumor, or in different tumor sites of the same patient. The challenge is to identify this heterogeneity, as it has emerged as the most common cause of ‘treatment resistance’, to current therapeutic agents. We have focused our discussion on ‘Prostate Cancer’ and ‘Neuroendocrine Tumors’, and looked at the established methods for demonstrating heterogeneity, each with its advantages and drawbacks. Also, the available theranostic radiotracers targeting PSMA and somatostatin receptors combined with targeted systemic agents, have been described. Lu-177 labeled PSMA and DOTATATE are the ‘standard of care’ radionuclide therapeutic tracers for management of progressive treatment-resistant prostate cancer and NET. These approved therapies have shown reasonable benefit in treatment outcome, with improvement in quality of life parameters. Various biomarkers and predictors of response to radionuclide therapies targeting TH which are currently available and those which can be explored have been elaborated in details. Imaging-based features using artificial intelligence (AI) need to be developed to further predict the presence of TH. Also, novel theranostic tools binding to newer targets on surface of cancer cell should be explored to overcome the treatment resistance to current treatment regimens.http://www.mdpi.com/journal/cancerspm2021Nuclear Medicin

Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer

Aim: The aim of this study was to investigate the feasibility of developing a deep learning (DL) algorithm for classifying brain metastases from non-small cell lung cancer (NSCLC) into epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement groups and to compare the accuracy with classification based on semantic features on imaging. Methods: Data set of 117 patients was analysed from 2014 to 2018 out of which 33 patients were EGFR positive, 43 patients were ALK positive and 41 patients were negative for either mutation. Convolutional neural network (CNN) architecture efficient net was used to study the accuracy of classification using T1 weighted (T1W) magnetic resonance imaging (MRI) sequence, T2 weighted (T2W) MRI sequence, T1W post contrast (T1post) MRI sequence, fluid attenuated inversion recovery (FLAIR) MRI sequences. The dataset was divided into 80% training and 20% testing. The associations between mutation status and semantic features, specifically sex, smoking history, EGFR mutation and ALK rearrangement status, extracranial metastasis, performance status and imaging variables of brain metastasis were analysed using descriptive analysis [chi-square test (χ2)], univariate and multivariate logistic regression analysis assuming 95% confidence interval (CI). Results: In this study of 117 patients, the analysis by semantic method showed 79.2% of the patients belonged to ALK positive were non-smokers as compared to double negative groups (P = 0.03). There was a 10-fold increase in ALK positivity as compared to EGFR positivity in ring enhancing lesions patients (P = 0.015) and there was also a 6.4-fold increase in ALK positivity as compared to double negative groups in meningeal involvement patients (P = 0.004). Using CNN Efficient Net DL model, the study achieved 76% accuracy in classifying ALK rearrangement and EGFR mutations without manual segmentation of metastatic lesions. Analysis of the manually segmented dataset resulted in improved accuracy of 89% through this model. Conclusions: Both semantic features and DL model showed comparable accuracy in classifying EGFR mutation and ALK rearrangement. Both methods can be clinically used to predict mutation status while biopsy or genetic testing is undertaken

Target Heterogeneity in Oncology: The Best Predictor for Differential Response to Radioligand Therapy in Neuroendocrine Tumors and Prostate Cancer

Tumor or target heterogeneity (TH) implies presence of variable cellular populations having different genomic characteristics within the same tumor, or in different tumor sites of the same patient. The challenge is to identify this heterogeneity, as it has emerged as the most common cause of ‘treatment resistance’, to current therapeutic agents. We have focused our discussion on ‘Prostate Cancer’ and ‘Neuroendocrine Tumors’, and looked at the established methods for demonstrating heterogeneity, each with its advantages and drawbacks. Also, the available theranostic radiotracers targeting PSMA and somatostatin receptors combined with targeted systemic agents, have been described. Lu-177 labeled PSMA and DOTATATE are the ‘standard of care’ radionuclide therapeutic tracers for management of progressive treatment-resistant prostate cancer and NET. These approved therapies have shown reasonable benefit in treatment outcome, with improvement in quality of life parameters. Various biomarkers and predictors of response to radionuclide therapies targeting TH which are currently available and those which can be explored have been elaborated in details. Imaging-based features using artificial intelligence (AI) need to be developed to further predict the presence of TH. Also, novel theranostic tools binding to newer targets on surface of cancer cell should be explored to overcome the treatment resistance to current treatment regimens

Intense focal Fluoro-deoxyglucose uptake in the lungs with no corresponding computed tomography abnormality

Scenario such as uptake of Fluoro-deoxyglucose (FDG) with no corresponding abnormality on computed tomography (CT) is encountered in case of brown fat uptake. However, it is rarely encountered in the lung parenchyma. We report one such case of a focal FDG uptake in the lung parenchyma with no corresponding CT abnormality, in a treated case of hypopharyngeal cancer

Reduced Order Modeling Methods for Aviation Noise Estimation

A key enabler for sustainable growth of aviation is the mitigation of adverse environmental effects. One area of concern is community noise exposure at large hub airports serving growing population centers. Traditionally, community noise exposure is computed using noise contours around airports, which requires knowledge of a large dataset pertaining to the air traffic operations at the airport of interest. Due to the underlying variability in real-world aircraft operations, numerous assumptions need to be made which adversely affect the accuracy of the model. Reduced-Order Modeling (ROM) methods provide a new framework for the retention of a large number of these parameters, thus improving model speed and accuracy. In this work, a proper orthogonal decomposition in conjunction with a response surface methodology-based surrogate model is used to create a rapid noise assessment model. Validation is performed against results obtained from the aviation environmental design tool with quantitative error metrics and visual contour comparisons. Obtained results are encouraging and motivate further work in this area with other ROM methods. ROM based models for noise assessment expand the solution space for noise mitigation strategies which can be evaluated, and therefore can lead to novel solutions which cannot be found with traditional modeling methods

Reduced Order Modeling Methods for Aviation Noise Estimation

A key enabler for sustainable growth of aviation is the mitigation of adverse environmental effects. One area of concern is community noise exposure at large hub airports serving growing population centers. Traditionally, community noise exposure is computed using noise contours around airports, which requires knowledge of a large dataset pertaining to the air traffic operations at the airport of interest. Due to the underlying variability in real-world aircraft operations, numerous assumptions need to be made which adversely affect the accuracy of the model. Reduced-Order Modeling (ROM) methods provide a new framework for the retention of a large number of these parameters, thus improving model speed and accuracy. In this work, a proper orthogonal decomposition in conjunction with a response surface methodology-based surrogate model is used to create a rapid noise assessment model. Validation is performed against results obtained from the aviation environmental design tool with quantitative error metrics and visual contour comparisons. Obtained results are encouraging and motivate further work in this area with other ROM methods. ROM based models for noise assessment expand the solution space for noise mitigation strategies which can be evaluated, and therefore can lead to novel solutions which cannot be found with traditional modeling methods

PET reconstruction artifact can be minimized by using sinogram correction and filtered back-projection technique

Filtered Back-Projection (FBP) has become an outdated image reconstruction technique in new-generation positron emission tomography (PET)/computed tomography (CT) scanners. Iterative reconstruction used in all new-generation PET scanners is a much improved reconstruction technique. Though a well-calibrated PET system can only be used for clinical imaging in few situations like ours, when compromised PET scanner with one PET module bypassed was used for PET acquisition, FBP with sinogram correction proved to be a better reconstruction technique to minimize streak artifact present in the image reconstructed by the iterative technique