Results: Breast, skin, colorectal, stomach and thyroid cancers were the most common cancers within the evaluated period of time in Isfahan Province. Colorectal cancer with an annual average total cost of 110,510,720 IRR (Rials) per patient was the most expensive cancer during the evaluated time period while thyroid cancer with an annual average total cost of 40,791,123 IRR per patient was the least costly cancer within the evaluated time period in Isfahan among the five most common cancers, considering the chemotherapy medicines cost. The highest cost in the colorectal cancer was due to the drug cetuximab distributed under the trade name Erbitux®. Regardless of the cancer type, the mean annual total cost of chemotherapy drugs per patient within the considered period of time calculated to be 96,307,145 IRR.
Conclusion: The chemotherapy cost of the common cancers was high with an annual average of more than 96 million IRR (Rials) per patient, within the considered time period. This was particularly true for colorectal cancer with an annual average cost of more than 110 million Rials. |
Conclusion: In this study, we investigated the epidemiological and clinical features of neck masses in Kerman. It is obvious that smoking is an important risk factor for neck mass malignancies. Also, the present study revealed that the incidence of malignant tumors increased with age.
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Conclusion: In the present study, the most common type of vasculitis diagnosed in children in eastern Iran was reported by Henoch-Schonlein and Kawasaki respectively, which was completely different from the most common types of vasculitis in adulthood and indicated the importance of age in diagnosing the type of vasculitis. The necessity of clinical suspicion of these two diseases in children with skin rashes, along with matching with other clinical findings, is undeniable.
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Methods: This cross-sectional study was conducted on all files of patients admitted to Qaem Hospital in Mashhad City, Iran, in a period of 10 years from March 2009 to February 2018 with a definitive diagnosis of benign or malignant tumors of the CNS, including tumors of the brain, cerebellum, spinal cord, or meningeal membranes. Information sources included the patients' physical files and the hospital information system (HIS). The statistical software SPSS version 28.0 for Windows (IBM SPSS, Armonk, New York, USA) was used for the statistical analysis.
Results: In total, 775 patients with benign and 771 patients with malignant CNS tumors were included in the study. Regarding epidemiological aspects of benign tumors, the incidence rate of women was almost twice that of men (68.47% versus 31.53%), with an overall average age of 45.31±19.81 years. The most common benign tumors were meningioma (72.77%), followed by schwannoma (13.67%). Regarding malignant brain tumors, the mean age of affected patients was 36.64±19.67 years, with males accounting for 53.04% of cases and females for 46.96%. The most frequent type of tumor was glioblastoma (32.68%), followed by diffuse astrocytoma (16.47%). Both benign and malignant CNS tumors were associated with significant hospital mortality; in-hospital mortality rates for benign and malignant tumors were 10.1% and 17.5%, respectively. Tumor type and its grade were the main determinants of early death in malignant CNS tumors. Conclusion: The epidemiological characteristics of benign and malignant tumors in our study community were similar to the reports presented in other communities. Knowledge of these characteristics provides the possibility of managing patients and reducing morbidity and mortality related to these tumors. |
Methods: This study used machine learning systems and similarity metrics to determine the behavior pattern of COVID-19 in different seasons of the year. The location of research was the Mousa ibn Ja'far Hospital in Mashhad, and the time was from May 2020 to August 2021. The symptoms of affected patients were compared with the compiled dataset, and the similarity of patients was prepared in a similarity matrix, and the Jaccard correlation coefficient was calculated on the data. Finally, the analysis of strains from the beginning of emergence to the latest strain was examined. The performance indicators of the algorithm in the Jaccard similarity method showed a recall metric with a value of 0.94, a precision metric with a value of 1, an F1 score with a value of 0.86, and remove accuracy metric with a value of 0.76. The most important factors in the investigation include white blood cells, platelets, RT-PCR, CT SCAN, shortness of breath, fever, SPO2, and respiratory rate.
Results: The transmission of the COVID-19 virus depends on several factors, including human interaction. The evidence of the collected data shows that people with COVID-19 have low lymphocyte count and it is very consistent with the results of recent studies. Due to the lack of a dataset, a comparative study was conducted and a dataset was collected. Conclusion: This study, leveraging machine learning algorithms, identified a clear seasonal correlation in the spread of COVID-19. Considering geographical and seasonal variations among patients, distinct symptoms were observed in each season corresponding to the prevalent strain during that period. |
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