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Cost-effectiveness of on-demand rFVIIa vs prophylactic emicizumab in hemophilia a with inhibitors: clinical, QoL, and ICER-based field insights
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Abstract<sec> <title>Objective

To evaluate the cost-effectiveness of emicizumab compared to recombinant activated factor VII (rFVIIa) in Iraqi patients with hemophilia A and inhibitors.

Method

A retrospective cost-effectiveness analysis was conducted on 46 male patients with hemophilia A and inhibitors treated at a public children’s hospital in Baghdad. Data collection was conducted between November 2024 and March 2025. Clinical and economic data were retrospectively collected for a 12-month follow-up for each of rFVIIa and then emicizumab, including bleeding episodes, emergency visits, treatment costs, and health-related quality of life assessed via EQ-5D-5L (adults) and EQ-5D-Y-3 L proxy (children). Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios were calculated.

Results

Emicizumab improved mean utility scores from 0.10 to 1.00 in children and from 0.32 to 0.89 in adults, corresponding to an incremental cost of –$2726.36 and –$4304.78 per QALY, respectively (indicating cost savings). Annual bleeding episodes dropped from 8.70 to 0, saving $282.04 per episode. Hospitalization costs decreased significantly, resulting in a total saving of $286650.41 per hospitalization prevented. Use of emicizumab also reduced overall healthcare resource utilization, eliminating emergency department visits, and minimizing diagnostic procedures.

Conclusion

Emicizumab delivers substantial clinical and economic benefits over rFVIIa. Its capacity to enhance quality of life while reducing treatment costs positions it as a cost-effective option for adults and children with hemophilia A and inhibitors in resource-constrained settings. Health authorities should prioritize emicizumab over rFVIIa for patients with hemophilia A and inhibitors, due to its superior efficacy and cost-effectiveness.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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Publication Date
Sat Jul 01 2023
Journal Name
Int. J. Advance Soft Compu. Appl,
Arabic and English Texts Encryption Using Proposed Method Based on Coordinates System
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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Tue Feb 24 2026
Journal Name
Baghdad Science Journal
EEG Lossless Signal Compression Based on Magnitude Classification and Run Length Encoding
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Mon Jun 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
SEQUENCE STRATIGRAPHY AND PALEOENVIRONMENT OF AALIJI FORMATION IN BAI HASSAN OIL FIELD IN KIRKUK PROVINCE, NORTHERN IRAQ
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The Aaliji Formation in wells (BH.52, BH.90, BH.138, and BH.188) in Bai Hassan Oil Field in Low Folded Zone northern Iraq has been studied to recognize the palaeoenvironment and sequence stratigraphic development. The formation is bounded unconformably with the underlain Shiranish Formation and the overlain Jaddala Formation. The microfacies analysis and the nature of accumulation of both planktonic and benthonic foraminifera indicate the two microfacies associations; where the first one represents deep shelf environment, which is responsible for the deposition of the Planktonic Foraminiferal Lime Wackestone Microfacies and Planktonic Foraminiferal Lime Packstone Microfacies, while the second association represents the deep-sea environme

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Strategic intuition and its role in achieving the efficiency of political marketing Field Study in Babil Governorate
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Because of the new political stage that Iraq is living in, which called on researchers to choose the subject of political marketing and increase its effectiveness through strategic intuition. The problem of research was reflected in the following question: How can strategic intuition be used to achieve efficiency in marketing marketing to achieve voter acceptance and achieve political success later on? ).

The research derives its importance from the fact that it is related to the developments in the concepts and areas of marketing in various fields, and it has a role in identifying the gain of new markets, where it is specialized to provide a political product and identify the mechanism of marketing the p

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