Bacterial meningitis is one of the harmful and deadly infectious diseases, and any delay in its treatment will lead to death. In this paper, a prognostic model was developed to predict the risk of death amongst probable cases of bacterial meningitis. Our prognostic model was developed using a decision tree algorithm on the national meningitis registry of the Iranian Center for Disease and Prevention (ICDCP) containing 3,923 records of meningitis suspected cases in 2018–2019. The most important features have been selected for the model construction. This model can predict the mortality risk for the meningitis probable cases with 78% accuracy, 84% sensitivity, and 73% specificity. The identified variables in prognosis the death included age and CSF protein level. CSF protein level (mg/dl) <= 65 versus > 65 provided the first branch of our decision tree. The highest mortality risk (85.8%) was seen in the patients >65 CSF protein level with 30 years < of age. For the patients <=30 year of age with CSF protein level >137 (mg/dl), the mortality risk was 60%. The prognostic factors identified in the present study draw the attention of clinicians to provide early specific measures, such as the admission of patients with a higher risk of death to intensive care units (ICU). It could also provide a helpful risk score tool in decision-making in the early phases of admission in pandemics, decrease mortality rate and improve public health operations efficiently in infectious diseases.
Background and Purpose:Invasive fungal infections cause morbidity and mortality in patients with hematologic malignancies and immunosuppression. Although these infections are commonly caused by Candida and Aspergillus species, infections caused by Mucoralean fungi are also on a growing trend. The definitive diagnosis of mucormycosis includes visualization of non-septate hyphae on pathology or growth of Mucoralean fungi culture. Polymerase chain reaction (PCR) is used to diagnose mucormycosis from paraffin blocks; however, it yields discrepant results in diagnosis of mucormycosis from blood samples. In the current study, we sought to examine the efficiency of PCR test for the diagnosis of mucormycosis and aspergillosis.Materials and Methods:Thirty-one patients with suspected fungal sinus infection were recruited from the Hematology-Oncology unit in Taleghani Hospital, Tehran, Iran. DNA was extracted and semi-nested PCR was performed.Results:PCR was reported negative for all the 31 serum samples. Our assay had a sensitivity of 1.3 ng and 12 pg for Mucoralean and Aspergillus species, respectively.Conclusion:Using serum PCR, we detected Aspergillus and Mucoralean species in patients with suspected fungal sinus infection. While this test may have utility in diagnosis directly from biopsy site, it appears unreliable for use as a noninvasive blood test.
Background: Infection by certain types of human papilloma virus (HPV) is known as a causal and essential factor for cervical cancer, the second most common malignancy in women around the world.
IntroductionThe Coronavirus disease 2019 (COVID-19) pandemic has caused irreparable damage to the world. In order to prevent the spread of pathogenicity, it is necessary to identify infected people for quarantine and treatment. The use of artificial intelligence and data mining approaches can lead to prevention and reduction of treatment costs. The purpose of this study is to create data mining models in order to diagnose people with the disease of COVID-19 through the sound of coughing.MethodIn this research, Supervised Learning classification algorithms have been used, which include Support Vector Machine (SVM), random forest, and Artificial Neural Networks, that based on the standard “Fully Connected” neural network, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) recurrent neural networks have been established. The data used in this research was from the online site sorfeh.com/sendcough/en, which has data collected during the spread of COVID-19.ResultWith the data we have collected (about 40,000 people) in different networks, we have reached acceptable accuracies.ConclusionThese findings show the reliability of this method for using and developing a tool as a screening and early diagnosis of people with COVID-19. This method can also be used with simple artificial intelligence networks so that acceptable results can be expected. Based on the findings, the average accuracy was 83% and the best model was 95%.
BackgroundHemophilic patients require long-life intravenous infusion of factor concentrates to treat bleedings. This could increase the risk of transmission of blood-borne infections like hepatitis C.ObjectivesThe current study was aimed at investigating the immunity status against hepatitis A in hemophilic patients in south Khorasan and evaluating the necessity of hepatitis A vaccination for this population.Patients and MethodsA cross-sectional descriptive study was conducted between 2014 and 2015 on all hemophilic patients of south Khorasan province, Iran (n = 108) for anti-HAV total, anti- HCV, HBs-Ag, anti-HIV, and anti-HTLV-I /II. Note that no one had already received a hepatitis A vaccine.ResultsAs our results show, 77.8% of the participants (59% under 20 and 88.4% above 20 years old) were seropositive for anti-HAV total; 20.4% and 2.8% (three patients) of the cases were anti-HCV positive and anti-HTLV-1 positive, respectively, while none of the subjects were HBS-Ag or HIV-Ab positive. Seventeen of the patients (15.75%) showed a co-infection of HAV with HCV, and five HCV-infected patients (22.73%) had no immunity against hepatitis A. There was a significant relationship between age, rural life, and anti-HAV positive state in our patients (P < 0.001). No significant relationship between positive anti-HAV status and sex (P = 0.16), severity of hemophilia (P = 0.23), and infection with HIV, HCV, HTLV-1, and hepatitis B (P > 0.05) was detected.ConclusionsMore than 40% of the hemophilic patients under 20 years of age in the present study had no immunity against hepatitis A, and 23% of hepatitis C patients had not had a hepatitis A co-infection yet. Since hepatitis A can show a fulminant course in hepatitis C patients, vaccination against hepatitis A seems necessary in hemophilic patients in the region.
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