Investigating the association of acute kidney injury (AKI) with COVID-19 mortality using data-mining scheme

COVID-19 has caused significant challenges in kidney research and disease management. Data mining techniques such as logistic regression (LR) and decision tree (DT) were used to model data. All analyses were performed using SPSS 25 and Python 3. The incidence of acute kidney injury (AKI) was 14.1% and the overall mortality risk was 13% among COVID-19 patients. The mortality was associated with, AKI, age, marital status, smoking status, heart failure, chronic obstructive pulmonary disease, malignancy, and SPO2 level using LR. The accuracy, sensitivity, specificity, and area under the curve of the DT (and LR) classifier were 70% (85%), 73% (75%), 78% (79%), and 77% (81%), respectively. Based on the DT model, the variable most significantly associated with COVID-19 mortality was AKI followed by age, high WBC count, BMI, and lymphocyte count. It was concluded that the incidence of AKI was high, and AKI was identified as one of the important factors that played an effective role in mortality due to COVID-19.

Investigation of hand muscle fatigue and its influential factors in manual tasks

Muscle fatigue (MF) can lead to musculoskeletal disorders (MSDs) in the long term; however, it can be managed if the causes are well known. This study aimed to examine the grip force (GF) and grip fatigue (GFa) of employees with light, moderate and heavy manual tasks using a dynamometer and find their possible relationship with other factors. The nature of heavy manual tasks led to more experience of GFa and GF of the right hand. Moreover, the equal need for both hands in occupations with light and moderate manual tasks is the reason for more GFa in the left hand. In this primary study, the height, weight and age of subjects and their exposure to vibration had a decisive effect on GF. In order to determine the accurate effects of the aforementioned risk factors on MF, it is recommended for future studies to be performed on larger populations.

Isolation and identification of nontuberculous mycobacteria from specimens of lower respiratory tract of transplanted patients based on the evaluation of 16SrRNA gene

BACKGROUND

Nontuberculous mycobacteria are pervasive microorganisms and are often present as saprophytes in humans, animals, and the environment. Today, these bacteria are known as the most important environmental opportunists and, in the last decades, infections by nontuberculous mycobacteria have multiplied, due to increased immunodeficiency (cancer, transplant recipients, HIV).

STUDY DESIGN

This study aimed to investigate the infections by nontuberculous mycobacteria in transplanted patients.

METHODS

The study was performed on 57 samples from respiratory secretions of transplant recipients taken by standard methods. Nontuberculous mycobacteria were identified by culture method and molecular identities of clinical isolates were investigated by PCR amplification using 16SrRNA gene and sequence analysis and Blast of the sequences. Demographic data were evaluated by Spss software.

RESULTS

The prevalence of nontuberculous mycobacteria in transplant patients was 22.8%, the age of patients was between 23 and 52 years. The most common involvement of nontuberculous mycobacteria in our transplanted individuals were 6 strains of M avium-intracellulare Complex (42.87%), followed by 2 strains of M marinum (14.29%) and 1 strain each (7.14%) of M xenopi, M chelonae, M intracellulare, M kansasii, M simiae. At the conclusion of the tests, one final strain was identified as M tuberculosis (7.14%).

CONCLUSION

The prevalence of nontuberculous mycobacteria indicates their importance in the fate of these patients. The identification of nontuberculous mycobacteria is a neglected part of microbiology laboratories, due to the lack of sufficient facilities and the risk associated with their culture. Therefore developing routine methods for the identification of these infections appears to be critical, especially in hospitals with the transplantation ward.

Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers

OBJECTIVES

This study aimed to provide an empirical model of predicting low back pain (LBP) by considering the occupational, personal, and psychological risk factor interactions in workers population employed in industrial units using an artificial neural networks approach.

METHODS

A total of 92 workers with LBP as the case group and 68 healthy workers as a control group were selected in various industrial units with similar occupational conditions. The demographic information and personal, occupational, and psychosocial factors of the participants were collected via interview, related questionnaires, consultation with occupational medicine, and also the Rapid Entire Body Assessment worksheet and National Aeronautics and Space Administration Task Load Index software. Then, 16 risk factors for LBP were used as input variables to develop the prediction model. Networks with various multilayered structures were developed using MATLAB.

RESULTS

The developed neural networks with 1 hidden layer and 26 neurons had the least error of classification in both training and testing phases. The mean of classification accuracy of the developed neural networks for the testing and training phase data were about 88% and 96%, respectively. In addition, the mean of classification accuracy of both training and testing data was 92%, indicating much better results compared with other methods.

CONCLUSION

It appears that the prediction model using the neural network approach is more accurate compared with other applied methods. Because occupational LBP is usually untreatable, the results of prediction may be suitable for developing preventive strategies and corrective interventions.

Should chronic treatment-refractory akathisia be an indication for the use of clozapine in schizophrenic patients?

BACKGROUND

Clozapine, an atypical neuroleptic, is an effective medication in a subgroup of schizophrenic patients who have either failed to respond to the typical neuroleptics or experienced intolerable side effects such as neuroleptic malignant syndrome and disabling tardive dyskinesia. Its efficacy for persistent and disabling akathisia is less clear. Akathisia, especially the chronic and disabling form, can be a treatment dilemma for the clinician and the patient.

METHOD

We describe three representative case illustrations of schizophrenic patients who had severe, persistent treatment-resistant akathisia. Two of them had refractory psychoses and the third had multiple disabling side effects during treatment with typical neuroleptics. Two had tardive dyskinesia. These patients were treated with clozapine while other neuroleptics were discontinued.

RESULTS

During a 2-year follow-up, these patients made impressive social and vocational strides coinciding with a fairly rapid remission of akathisia (under 3 months) and a lesser though notable improvement in the psychoses. Tardive dyskinesia also remitted, though over a period of 6 to 12 months.

CONCLUSION

Our experience leads us to suggest a trial of clozapine in a subgroup of schizophrenic patients, who in addition to refractory psychoses have persistent disabling akathisia. However, given the risk of agranulocytosis with clozapine, we suggest that the usual treatment strategies for akathisia be tried before clozapine is initiated in the approved manner. Future controlled trials of clozapine that specifically investigate persistent akathisia may answer this question more conclusively.

Haemoglobin Arya: alpha 2-47 (CD5), aspartic acid yields asparagine

A new haemoglobin variant (haemoglobin Arya), is described from an Iranian female. The substitution is at residue 47 (CD5) of the alpha chain in which aspartic acid has been substituted by asparagine. The presence of haemoglobin Arya was not associated with clinical symptoms. This variant has normal stability at 50 degrees C, but is slightly unstable when tested at 55 degrees C.