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Background: Many aspects of the severe acute respiratory syndrome coronavirus 2 (SARSCoV2) pandemic in 2019 have been unclear, especially in newborns, and reports of neonatal diseases are usually associated with perinatal infection. Objective(s): The purpose of this study was to evaluate clinical and para-clinical manifestations in newborns that contracted the infection after birth. Method(s): This observational research was conducted from October 2020 to March 2022 to examine postnatal SARSCoV2 infection in infants admitted to the NICU or neonatal ward at the Children's Medical Center in Tehran, Iran. Inclusion in the study was open to neonates who had positive RT-PCR results postnatally. Result(s): In total, 55 newborns were confirmed to have postnatal SARSCOV2. Fever was the most frequently observed symptom, with 35 (61%). Necrotizing enterocolitis was seen in 18% of neonates, and 30% of them were preterm. Neutropenia was seen in 34% of cases, with five cases having severe neutropenia. All neonates had a normal platelet count. Twenty percent of patients showed C-reactive protein higher than 6 mg/L. Two newborns had co-existing bacterial urinary tract infections. Our neonates didn't require antiviral, anticoagulant, or corticosteroid medications, and they recovered while receiving only supportive care. Everyone in the group of newborns was discharged without complications, and there were no deaths. Conclusion(s): The high rate of fever, high C-reactive protein, and neutropenia in SARSCoV2 neonates suggests that more observational research is needed to compare these symptoms to bacterial sepsis to avoid the overuse of antibiotics in these patients.Copyright © 2023, Author(s).
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After the Ministry of the health of Iran officially announced widespread of COVID-19 on 19 February 2020, our attention focused on novel coronavirus. In our case, a2-day- old neonate shows symptoms of sepsis. The main presentation was hypothermia and desaturation. The mother was COVID-19 positive with an active cough. The PCR of the neonate was negative. We don't claim that the neonate is affected by COVID-19, but this may be an atypical form of sepsis in neonates with positive mothers following COVID-19. A2-day- old female neonate with a gestational age of 40 weeks and a birth weight of 2370 grams was born via the cesarean route from a mother who was a 34-year-old primigravida woman without any history of disease during pregnancy. Two days before delivery, the mother had malaise and dry cough. She was diagnosed as a COVID-19 positive case based on RT-PCR after delivery. On the second day after birth, the parents brought the baby to the emergency room of the children's medical center hospital with complaints of poor feeding, poor sucking and decreased urination. Physical examination revealed the following signs;hypothermia;T=36C, diminished primitive reflexes, hypotonia, and oxygen desaturation until 85% without respiratory distress that increased to 98% with oxy hood. We admitted and treated her early-onset sepsis and discharged in excellent condition.Early-onset sepsis as defined is a clinical state that is transferred from mother. The presentations in our case maybe a new form of clinical sepsis following a mother with COVID-19. We don't claim that our case is COVID-19 positive but in neonates with affected mother's insidious symptoms should be in concern. Copyright © 2022 Tehran University of Medical Sciences.Published by Tehran University of Medical Sciences.
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The Coronavirus disease 2019 (COVID-19) pandemic is being addressed through RT-PCR, a frontline diagnostic technique. We evaluated gene expression patterns to improve the accuracy and sensitivity of current diagnostic tests. We downloaded relevant next-generation sequencing (NGS) data from the Sequence Read Archive (SRA) database, checked for quality, and mapped them onto the target reference sequence. It was determined that ORF1ab, N, S, and ORF8 genes are mainly expressed based on the results of the quantitative evaluation after normalization by HPRT and elimination of insufficient expression data. ORF8, ORF3a, and M genes were found to have higher expression values than the E gene as a routine RT-PCR detector gene (p*0.05). M gene expression values are also close to ORF8 values. Taking into account the importance of differential expression of genes in the design of diagnostic kits as well as the findings of from this study, it is likely that the M gene is worth further investigation due to its high expression and low mutation rate.
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Global aging, the need for continuous high-quality services, and the recent COVID-19 pandemic have caused many sectors to reduce in-person contact between individuals where possible, and to instead use remote communication technology. With increased robot use replacing in-person interventions, ethical considerations arise. The benefits of robotic technology must be weighed against the possibility of harm to humans. The first rules of roboethics were written by Isaac Asimov in 1942, but these pre-date the range of robotic applications used today. There is no central agency for oversight in Canada, although universities and funding organizations have developed guidelines. Roboethical considerations include data use and privacy, the common good, and safety. Humans may potentially form emotional bonds with robots. Loss of jobs to automation is also a concern, particularly when many workers have suffered job losses due to the pandemic. Some health care services have switched to a remote care model, to reduce the spread of COVID-19. Remote hand rehabilitation of patients with brain injury is possible with iManus. Using a portable smart-glove technology, patients practice rehabilitative hand movements that are analyzed remotely through a sensor that offers instantaneous feedback. A therapist monitors their patient's progress remotely and designs individualized programs. This technology benefits humanity by improving access to care for patients globally. The importance of data security and privacy is emphasized. As patient progress will be monitored by a human (a therapist), the safety of iManus is not a concern. The principles discussed in this paper can help researchers and engineers design ethical robotics in remote health care settings.
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Background and purpose: Disease registry of Coronavirus disease 2019 (COVID-19) as an emerging global health threat could create a suitable research context, identify various aspects of the disease from symptoms to laboratory diagnoses, and determine effectiveness of treatment. The present study aimed to design and implement COVID-19 registry in Sari Imam Khomeini Hospital and investigated preliminary results. Materials and methods: At first stage, to design the disease registry, a strategy committee was established consisting of experts involved in COVID-19. Variables determined by members of the registry strategy committee included demographic findings, patients' vital signs, comorbidity, laboratory findings, diagnostic test results, disease forms, complications, patients' prognosis, and medical interventions on admission and at the time of discharge. Then, a web based software was designed in Structured Query Language (SQL) to record the information. The study population included all patients attending Sari Imam Khomeini Hospital with clinical and molecular diagnosis of COVID-19.
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Background and purpose: The association between ABO blood types and Coronavirus disease 2019 (COVID-19) have been investigated in several studies but there are inconsistencies in results. The purpose of this study was to investigate the association between ABO blood types and COVID-19 infection based on serologic results. Materials and methods: A cross-sectional seroepidemiologic study was carried out in 1504 people living in Mazandaran province, north of Iran. Blood samples were drawn to determine blood groups. Also, IgG and IgM antibodies were measured by ELISA. Data analysis was done using Chisquare, Fisher’s exact test, univariate and multivariate logistic regression analyses in SPSS V25. Results: The frequency of IgG positive among blood groups A, B, AB, and O was 12.7%, 11.8%, 9.4%, and 9.6%, respectively. After adjusting for suspicious confounding factors, the odds ratio of COVID-19 infection was 1.19 (95% CI:0.85-1.67) in blood group A, 1.33 (95% CI:0.94-1.87) in blood group B, 0.82 (95% CI:0.44-1.55) in blood group AB, and 0.70 (CI 95%:0.50-0.98) in blood group O based on serologic results (IgG+/IgM+). Conclusion: The odds ratio for COVID-19 was significantly lower (30%) in blood group O compared to other blood groups, so blood group O can be considered as a protective factor against COVID-19.
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Background and purpose: Vitamin D deficiency is highly prevalent in Iran. Death toll due to the Coronavirus Disease 2019 (COVID-19) is high in this country. The purpose of the present investigation was to provide more information on the relationship between serum levels of vitamin D in confirmed cases of COVID-19 in north of Iran. Materials and methods: This cross-sectional descriptive study was performed in COVID-19 patients (n=80) attending Sari Imam Khomeini Hospital, Iran 2020, who were confirmed for COVID-19 infection with CT-Scan or RT-PCR. Seventy healthy individuals were also examined as the control group. SPSS V19 was applied for data analysis. Results: In this study, 80 patients with COVID-19 (mean age: 57.22 ± 17.44 years old) and 70 healthy individuals (mean age: 48.69 ± 12.99 years) were studied. There were 38 and 35 males in these two groups, respectively. Serum Vitamin D levels were significantly lower in patients with COVID-19 than those in the control group (18.72 ± 12.53 vs. 30.86 ± 15.19 ng/ml, P< 0.001). Conclusion: This study showed that serum levels of Vitamin D were lower in patients with COVID-19 than healthy individuals and frequency of Vitamin D deficiency was higher in these patients. Hence, further studies are needed to clarify the role of serum Vitamin D concentrations in patients with COVID-19 infection.
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Objective: To determine the seroprevalance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in the general population of Mazandaran province in Iran and to estimate the percentage of asymptomatic, mild, and severe infections. Methods: We chose 1 588 inhabitants of Mazandaran province with cluster sampling. We measured their SARS-CoV-2 immunoglobulin M (IgM) and immunoglobulin G (IgG) serum levels. Demographics, risk factors, and symptoms were collected. The seroprevalence of SARS-CoV-2 was calculated by age and city and the World Health Organization (WHO) protocol and further stratified by demographic variables and risk factors. Finally, we identified the symptoms and factors related to COVID-19 with logistic regression. Results: Two hundred subjects (12.59%) were tested positive for either IgG or IgM. Until May 23, 2020, the prevalence of COVID-19 was 15.26% (95% CI: 12.97%-17.79%) based on direct standardization and WHO's standardized age groups. Based on multivariate logistic regression, the incidence of getting an infection increased by an average of 11.6% for every 10-year increase in age (OR=1.116, 95% CI: 1.008-1.236, P=0.035). Furthermore, those in contact with COVID-19 patients had a 66.1% higher risk of developing the disease (OR=1.661, 95% CI: 1.104-2.497, P=0.015). In addition, the chance of getting SARS-CoV-2 infection was almost four times higher in people who had consulted a doctor during the pandemic than those who had not (OR=3.942, 95% CI: 2.813-5.524, P<0.001). Conclusions: The prevalence of COVID-19 in Mazandaran province could be higher than the officially reported statistics based on diagnostic tests and clinical cases. There seems to be more asymptomatic or mild symptom cases than what was previously reported.
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Increase of stored data in medical databases needs allocative tools to get access to data, data mining, discover knowledge and efficient use of data. Medical and treatment fields are two examples of data mining tools to analyze massive data and predictive modelling. In medical sciences, prediction and precise-quick detection of multiple diseases has to reduced exprense and also save people's lives. Group based methods (Ensemble Methods) are approaches that use hybrid models to recover classification. Coronavirus (COVID-19) has killed many people around the world so far, and this could be a good reason to present a new model for diagnosing the disease using data mining algorithms. This research presents a hybrid model of basic data mining and hybrid algorithms according to information in medical and laboratory records of patients suffering Covid-19 in Emam-Reza (AS) hospital in Mashhad, Iran, to diagnose the sickness. The proposed method uses Ensemble base (hybrid) classifiers, where the general model can be used to provide diagnoses with higher precision rather than classifiers. To execute the proposed model, data mining tools including Rapid Miner 9.7 and Python 3.7 were used. This study used stacking classifiers composed of basic algorithms including simple baze, decision tree, K- nearest neighborhood backup vector machine for basic section and uses chaos jungle algorithm in stack section that has gained 86.5% accuracy for diagnosis of Covid-19.
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Neonates are vulnerable to COVID-19 infection. Its estimated rate in this age group is unknown. There is a robust transmission of COVID-19 from human-to-human. The result of all COVID-19 PCR tests on the amniotic fluid, placenta, cord, and breast milk was negative. The nasopharyngeal swab test of COVID-19 PCR in 56% of neonates was positive. 46.6% of neonates were asymptomatic, and in the others, the most common symptoms were: shortness of breath, tachypnea, cough, apnea, temperature instability, tachycardia. The possibility of vertical transmission (maternal-fetal) of COVID-19 is unknown. Because the most infected neonates with COVID-19 are asymptomatic, the transmission of the disease to other family members is very likely.
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COVID-19 is an illness caused by a novel coronavirus also known as severe acute respiratory syndrome coronavirus 2, which was first identified in the City of Wuhan, China. Since then, it has been declared as a global pandemic by the World Health Or-ganization. The late diagnosis of COVID-19 patients makes the fast spreading of the virus across the globe. Purpose: Thus, the solution to slow down the spread of this virus would be an expert system that will be able to diagnose COVID-19 patients and produce results instantly. This paper discusses how a knowledge-based expert system can help to diagnose or detect COVID – 19 in the early stage itself and get the result immediately without any delay. © IJCRR.
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Background: Coronavirus is a single-stranded RNA virus, causing an epidemic of pneumonia and acute respiratory distress syndrome (ARDS) worldwide in late 2019. Objectives: In addition to the clinical symptoms, laboratory diagnosis can greatly help diagnose the diseases;therefore, this study aimed to analyze laboratory parameters in patients with COVID-19. Methods: In this cross-sectional study, the laboratory data of 2563 patients with COVID-19 admitted to hospitals affiliated with Mazandaran University of Medical Sciences were extracted from hospital information systems (HIS). The data were recorded on Excel and analyzed through t-test, chi-squared, and Fisher's exact tests in SPSS 19 at the significance level of P < 0.05. Results: Out of 2563 patients with a mean age of 55.1 +/- 16.7 years, 1409 (55%) were male, and 1154 (45%) were female with a mean age of 55.7 +/- 16.8, and 54.3 +/- 16.6 years, respectively. As the most frequent clinical findings, ESR, CRP, and LDH were increased by 83.5%, 71%, and 69.3% of the patients, respectively. Other research findings included lymphopenia, disturbed INR, abnormal SGOT, abnormal alkaline phosphatase (ALP), and increased lactate dehydrogenase (LDH), which were significantly higher in men than in women and was different between age groups. Conclusions: Conducting simple, convenient, and inexpensive laboratory tests can be helpful in the diagnosis of COVID-19.