Performance of Carbapenemase Nordmann-Poirel, Modified Carbapenem Inactivation, and EDTA Carbapenem Inactivation Methods for Detecting Carbapenem-Resistant Klebsiella pneumoniae Isolates.

Infections caused by carbapenem-resistant Klebsiella pneumoniae (CRKP) are a major threat to public health. Timely detection of CRKP will help treat patients with appropriate antibiotics. This study aimed to evaluate the performance of the carbapenemase Nordmann-Poirel (CarbaNP), modified carbapenem inactivation (mCIM), and EDTA carbapenem inactivation (eCIM) methods for the detection of CRKP. We compared the results of the three assays with that of real-time PCR. In total, 195 K. pneumoniae isolates, including 150 carbapenem-resistant and 45 carbapenem-susceptible isolates, were investigated. Carbapenem-resistance genes, such as blaKPC, blaNDM, blaVIM, blaIMP, and blaOXA-48-like, were identified using real-time PCR. Among the 150 CRKP isolates, 94 (62.7%) were positive for blaNDM, 29 (19.3%) were positive for blaOXA-48-like, and 27 (18%) were positive for both blaNDM and blaOXA-48-like. For detecting CRKP isolates, CarbaNP, mCIM, and eCIM showed 96.0%, 95.4%, and 96.7% sensitivity, respectively, and all three methods showed 100% specificity. All three phenotypic confirmatory tests are reliable for identifying CRKP, easy to perform, cost-effective, and can be incorporated with routine antibiotic susceptibility testing.

Metabolic syndrome - cardiac structure and functional analysis by echocardiography; a cross sectional comparative study.

OBJECTIVES: Metabolic syndrome (MS) is a collection of metabolic disorders including hyperglycemia, hypertension and dyslipidemia. The outcome of metabolic syndrome depends on structural changes in heart like increased left atrial size or increased left ventricular mass. This study was done to determine the echocardiography abnormalities in metabolic syndrome. METHODS: After obtaining informed consent, 75 subjects with metabolic syndrome and 75 controls were included in the study. 2D echo/M mode examination was performed for all. Aortic root, left atrial size, left atrial volume, septal wall thickness during systole (SWs) and diastole (SWd), posterior wall thickness during systole (PWs) and diastole (PWd), left ventricle dimension during systole (LVDs) and diastole (LVDd), and ejection fraction were measured. The values were compared between the groups. RESULTS: After adjustment for age, sex, smoking, alcohol and BMI; left ventricular diameter in systole and diastole was significantly more than controls (p<0.001); HR of 1.29 (95% CI 1.13-1.46), 1.29 (95% CI 1.15-1.45) respectively. Left ventricular mass and left atrial volume were increased significantly in subjects with metabolic syndrome (p<0.001); HR were 1.06 (95% CI 1.03-1.08), 1.13 (95% CI 1.06-1.19) respectively. Ejection fraction was low normal in subjects with metabolic syndrome compared to controls (p<0.05); HR 0.90 (95% CI 0.83-0.98). CONCLUSIONS: Cardiac abnormalities were common in subjects with metabolic syndrome, predominantly affecting the left ventricular mass, diameter and left atrial volume. Early life style modifications are essential to prevent these complications.

COVID-19 and Dementia; Hard to Forget Yet Haunting Forgetfulness!

The current pandemic has affected almost everyone worldwide. Although the majority of people survive the illness, bad cognitive repercussions might last a long time, resulting in a lower quality of life and disability, particularly in severe cases. We tried to understand and bring together the various possible mechanisms leading to dementia in COVID-19. The link between COVID-19 and dementia will help public health workers plan and allocate resources to provide better care for a community suffering from sickness and improve quality of life. A conceptual framework for care of infected people in the older age group and care of dementia people is proposed.

Association of Serum Magnesium with Insulin Indices in Patients with Type 2 Diabetes Mellitus.

Introduction: Magnesium has a direct impact on glucose metabolism since it is a cofactor for numerous energy-metabolizing enzymes. Hypomagnesemia has been linked to poor glycemic control and a range of diabetes-related long-term complications. This study aimed to assess the association between blood magnesium levels and insulin sensitivity indices in patients with type 2 diabetes mellitus (T2DM). Material and methods:Two hundred newly diagnosed T2DM patients aged over 40 years were recruited after excluding those with a history of heart failure, kidney illness, liver disease, hypothyroidism, ascites, pregnancy, tumors, and complications such as diabetic ketoacidosis. Fasting glucose, serum magnesium, serum insulin, serum urea and creatinine were measured. Patients were divided into two groups based on their serum magnesium levels. Results:There were no age or sex differences between the subjects of the two groups. Participants in the group with low magnesium had significantly high fasting blood sugar (FBS), postprandial blood sugar (PPBS), glycated hemoglobin (HbA1c), serum insulin, homeostasis model assessment-estimated insulin resistance (HOMA-IR) (P < 0.001). The multivariable logistic regression analysis showed significant associations with PPBS [odds ratio (OR) 0.98 (95% CI 0.97-0.99)], HbA1c [OR 0.05 (95% CI=0.005-0.55)] and creatinine [OR 0.004 (95% CI=0.00-0.074)]. Correlation statistics showed a negative correlation between magnesium and PPBS (r =-0.204), HOMA-IR (r = -0.819) and creatinine (r = -0.151). Conclusion:Serum magnesium levels have a negative correlation with FBS and PPBS, as well as HOMA-IR. It may well be essential to include serum magnesium level as a regular assessment in patients with diabetes mellitus.

Risk Assessment of COVID-19 Infection among the Elderly Population.

Introduction:Elderly patients are susceptible to COVID-19 infection. They usually present with atypical symptoms and multiple organ dysfunction. The poor outcome in elderly patients is due to multiple comorbidities, declining functional status, and frailty. This study aimed to assess the risk profile of COVID-19 infection in the elderly population. Materials and methods:Patients aged 60 years and above with COVID-19 positive by RT-PCR were included in the study. Patients' demographic data, co-morbidities and severity of illness, complete hemogram, blood sugar, renal, liver function test, lactate dehydrogenase, interleukin-6, ferritin, D-dimer were noted. Patients' outcome in terms of survival was observed. Results:The total count, neutrophil lymphocyte ratio, ESR, urea, creatinine, interleukin 6, D-dimer, and blood sugar value were significantly associated with non-survival even after adjustment for age and gender. Complications such as acute kidney injury (AKI), renal failure, acute respiratory distress syndrome, multiorgan dysfunction syndrome (MODS), and World Health Organization (WHO) severity were also associated with non-survival before and after adjustment for age and gender. On Cox regression survival analysis, . three co-morbidities had hazard ratio (HR) of 54.36 [95% CI 3.66 to 807.01], WHO severity had HR of 31.09 [95% CI 1.31 to 738.22], MODS had HR of 16.97 [95% CI 2.86 to 100.39], creatinine had HR of 8.44 [95% CI 1.99 to 35.77], AKI had HR of 6.71 [95% CI 1.11 to 40.56]. Conclusion:In elderly patients with COVID-19 infection, the presence of at least three co-morbidities, severity of infection by WHO criteria and presence of complications such as MODS, elevated creatinine and AKI were predictors of the survival rate and mortality.

Zika, Nipah and Kala-azar: Emerging lethal infectious diseases amid COVID-19 as an escalating public health threat in South India.

As of 6 June 2022, a sum 25,782 of active cases and 524,701 deaths due to Coronavirus disease-19 (COVID-19) have been recorded in India. Stewing in the flares of the pandemic, Kerala is entwined in the wrath of multiple emerging infectious diseases. India, a home to 1.3 billion people, recently faced a devastating second wave of COVID-19 during May of 2021, with a ruckus of chronic shortage of medicine, oxygen supplies, ventilators, besides, being challenged by secondary infections and chronic health ailments. The state of Kerala, alone contributes to 50% COVID-19 caseload, besides, recent simultaneous outbreaks of Zika Virus Disease (ZVD), Nipah Virus Disease (NiVD) and Kala-azar (black fever) on July 8, September 5 and 8, 2021 respectively. Syndemicity and a high case fatality rates of these highly contagious diseases coupled with post infection sequelae, overwhelm the already fragile healthcare system. Thus, these lethal infectious diseases along with an anticipated third wave of COVID-19 pose a serious public health threat in and around South India. With this narrative review, we aim to discuss the challenges that the emergence of intersecting outbreaks of Zika, Nipah, Kala-azar presents with, in the nation, amidst the global pandemic of COVID-19 and provide recommendations so as to help alleviate the situation. The syndemicity of COVID-19 with other infectious diseases, calls for adequate surveillance and monitoring of diseases' outbreaks. To avoid the worst situations like pandemic, the health ministry, public and private health stakeholders in India should strengthen the public healthcare delivery system and providence of quick medical facilities to control the rate of mortality and morbidity during outbreaks.

Artificial Intelligence-Based Portable Bioelectronics Platform for SARS-CoV-2 Diagnosis with Multi-nucleotide Probe Assay for Clinical Decisions.

In the context of the recent pandemic, the necessity of inexpensive and easily accessible rapid-test kits is well understood and need not be stressed further. In light of this, we report a multi-nucleotide probe-based diagnosis of SARS-CoV-2 using a bioelectronics platform, comprising low-cost chemiresistive biochips, a portable electronic readout, and an Android application for data acquisition with machine-learning-based decision making. The platform performs the desired diagnosis from standard nasopharyngeal and/or oral swabs (both on extracted and non-extracted RNA samples) without amplifying the viral load. Being a reverse transcription polymerase chain reaction-free hybridization assay, the proposed approach offers inexpensive, fast (time-to-result: ≤ 30 min), and early diagnosis, as opposed to most of the existing SARS-CoV-2 diagnosis protocols recommended by the WHO. For the extracted RNA samples, the assay accounts for 87 and 95.2% test accuracies, using a heuristic approach and a machine-learning-based classification method, respectively. In case of the non-extracted RNA samples, 95.6% decision accuracy is achieved using the heuristic approach, with the machine-learning-based best-fit model producing 100% accuracy. Furthermore, the availability of the handheld readout and the Android application-based simple user interface facilitates easy accessibility and portable applications. Besides, by eliminating viral RNA extraction from samples as a pre-requisite for specific detection, the proposed approach presents itself as an ideal candidate for point-of-care SARS-CoV-2 diagnosis.