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Showing 4 results for Masoomi
A survey on orbital fractures in an educational center
Farahvash Mr, Yegane Ra, Farahvash B, Sheidaeian M, Masoomi M,
Volume 67, Issue 3 (5 2009)
Abstract

Normal 0 false false false EN-GB X-NONE AR-SA MicrosoftInternetExplorer4 !mso]> ject classid="clsid:38481807-CA0E-42D2-BF39-B33AF135CC4D" id=ieooui> Background: Trauma is the 2nd cause of mortality in Iran, after cardiovascular diseases. In traumatic patients, head and neck and face skeletal fracture is common. The most common facial fracture is mandible fracture and the least common is frontal fracture. Complications due to orbital fracture are more devasting than the other fractures in face.
Methods: These descriptive cross sectional studies are designed on 92 patients with orbital fractures in a referral educational trauma center, Imam Khomeini hospital, Tehran, Iran. Sample size was the patients who referred to this hospital with orbital fracture during the ten years period (1986-2000).
Results: In this study 74 patients were male and 18 patients were female. Mean age of patients was 30 years. The most common cause of orbital fracture was motor vehicle accident which was seen in 38 patients.46 patients had fracture in left orbit and 44 patients in right. Isolated orbital fracture was seen in 38 patients and 54 patients had concomitant trauma and fracture in the other organs. Management of orbital fracture was reduction of displaced bone fragment and fixation for osteosynthesis. The most common methods for osteosynthesis was fixation with miniplate which used in 53 patients and then reconstruction of orbital floor and roof with autologus bone graft. The most common complications due to orbital fracture was related to eyes that were seen in 20 patients.
Conclusion: Face fractures are a piece of all problems in multiple trauma patients as the tip of iceberg. Concomitant injuries are the concealed part of this iceberg. Early detection of orbital fracture and immediate treatment that prevent the future complications and deformities due to orbital fractures.


How long it takes patients' initial statements of concerns? brief report
Ali Labaf , Rasoul Masoomi , Misaq Raeisi ,
Volume 73, Issue 8 (November 2015)
Abstract

Background: There is a concern by some doctors that not interrupting the patients' initial statements of concerns can lead to too long medical visits. Therefore, in this study, the duration of the patients' initial statements of concerns was studied. Methods: This descriptive cross sectional study was conducted from August to October, 2011 in the Emergency Department of Imam Khomeini Hospital in Tehran. 100 patients entered the study through convenience sampling. Based on a 5 level triage system Emergency Severity Index (ESI), patients who were not life-threatening conditions (level 5) entered the study and critically ill patients and foreign patients were excluded from the study. Demographic data of the patients and durations the patients' initial statements of concerns were recorded and measured. Results: Fifty-six percent of patients were men. 79 percent of them had academic degree less than diploma and most of them have Persian ethnicity (60 percent). The mean age of the participants was 37.09 (SD, 1.68). The mean durations of patients' initial statements was 71.60±2.37 seconds. The minimum time was 22.51 seconds and the maximum time was 206.51 seconds. There was significant difference between age (P=0.001, r=0.382) and gender (P=0.032, df=98, t= -2.17) with the durations of patients' initial statements. But education level (P=0.996, F (2, 97)=0.004) and ethnicity (P=0.266, F (6, 93)=1.3) did not have a significant effect on the durations of patients' initial statements. Conclusion: According to the findings of this study, duration of patients' initial statements of concerns is less than what which leads to an increase the time of medical visits.


Retinoblastoma treatment over time: a review article
Hassan Asadigandomani, Seyed Mohsen Rafizadeh, Elias Khalili Pour , Babak Masoomian,
Volume 81, Issue 4 (July 2023)
Abstract
Retinoblastoma is the most common primary malignant ocular malignancy in children. The management and treatment of retinoblastoma is a very complex process and requires attention to different aspects, such as the stage of the disease based on the International classification of retinoblastoma (ICRB) or International intraocular retinoblastoma classification (IIRC), the genetic status of the tumor and mutations, psycho-social factors of the family and society, cultural beliefs, and available economic resources. From the identification of this malignancy until the beginning of the 20th century (before the introduction of radiation therapy as one of the treatment options), enucleation was the only treatment option for this disease. In addition to not controlling metastatic and extensive features of the disease and increasing the chance of death in these cases, enucleation causes many adverse psychological and aesthetic complications in patients, and especially children, who are the main population affected by this disease. Tremendous progress has been made since the 20th century to identify and invent new methods to preserve the eyes and less invasive treatments (globe salvage treatments), and the set of efforts led to the inventing of new treatment methods such as radiation therapy, systemic chemotherapy, local treatments such as cryotherapy and thermotherapy, intra-arterial chemotherapy and intraocular chemotherapy. In summary, the set of treatments from the beginning until now has gone towards increasing survival, reducing the rate of enucleation and providing more targeted and less invasive treatments. Despite these advances, early diagnosis is the most important prerequisite for better outcomes. However, early detection is influenced by socioeconomic factors and is a major challenge, especially in low- and middle-income countries. In fact, the provision of advanced medical care in high-income areas has provided excellent survival, globe, and vision-saving rates. Unfortunately, these results do not hold true for medical systems in low- and middle-income areas, leading to poor patient outcomes. In this article, we briefly introduce various retinoblastoma treatment methods from the beginning of detection until now, and we assess the evolution of the treatment of this disease from the beginning until now, which has reduced the need for enucleation as a treatment for this disease.

The role of artificial intelligence in glaucoma: a review article
Zakieh Vahedian Ardakani , Mehran Zarei-Ghanavati , Hamid Riazi-Esfahani , Seyed Mehdi Tabatabaei , Mohammad Reza Mehrabi Bahar, Sadegh Ghafarian, Ahmad Masoomi,
Volume 83, Issue 1 (April 2025)
Abstract
Artificial intelligence (AI) has emerged as a transformative force in modern medicine, with ophthalmology standing at the forefront of its clinical integration. Among ophthalmic disorders, glaucoma—a leading cause of irreversible blindness worldwide—presents unique opportunities and challenges for AI-based solutions due to its chronic, progressive nature and reliance on multimodal data, including structural and functional assessments. This review article offers a comprehensive synthesis of the current and emerging roles of AI in the detection, monitoring, and management of glaucoma. AI algorithms, particularly deep learning and machine learning models, have demonstrated exceptional capabilities in interpreting fundus photographs, optical coherence tomography (OCT) images, and visual field data to identify glaucomatous damage. These systems often approach or even exceed the diagnostic performance of human experts. Moreover, AI has shown significant promise in facilitating large-scale population-based screening, improving early detection rates, and addressing disparities in access to subspecialty care, particularly in low-resource and remote settings. In the monitoring of disease progression, AI tools are being developed to detect subtle structural or functional changes over time, predict future visual outcomes, and support more precise and individualized treatment decisions. Despite these advancements, the widespread clinical adoption of AI in glaucoma care faces several critical barriers. Key limitations include poor generalizability of models across diverse populations, imaging devices, and clinical settings; scarcity of well-annotated, high-quality, and demographically representative datasets; and a lack of transparency and interpretability in algorithmic decision-making—commonly referred to as the “black box” problem. Ethical concerns, regulatory uncertainty, integration challenges within existing healthcare infrastructures, and medico-legal accountability also require thoughtful resolution before AI can be reliably deployed in clinical practice. This review critically evaluates the strengths, limitations, and real-world potential of AI technologies in glaucoma. It provides clinicians, researchers, and healthcare policymakers with a balanced and up-to-date perspective, highlighting promising avenues for future research, including explainable AI, federated learning, multi-modal data integration, and longitudinal validation studies. By fostering a deeper understanding of both the opportunities and challenges associated with AI, this article aims to guide the responsible, equitable, and evidence-based integration of AI into comprehensive glaucoma care.

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