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Risk Factors for Fistula Development Following Palatoplasty
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Purpose:

The aim of this study is to assess the influence of some risks factors on the fistula development after palatoplasty to improve the outcome of the patients

Patients and Methods:

A total of 48 patients (the males were 22, The females were 26) were included in this study. All the patients were examined weekly for the first month postoperatively to assess any breakdown in the wound by inspection and by asking the parents for any nasal regurgitation during fluids feeding.

Results:

The incidence of palatal fistula development after primary palatoplasty in this study was 12.5% (6\48). Occurrence of fistula was unrelated to the gender (P >0.5), but it was directly related to the age of patients (r = 0.98) and to the size of the cleft (r = 1). Fistula had occurred most likely in cases of Baradach 2 flap palatoplasty (83.3%) this was occurred especially when it was used for isolated cleft palate, but it was not associated with the type of the cleft (P >0.4). The surgeons experience and the use of prophylactic antibiotic were associated with the development of the fistula (P = 0.01 for both).

Conclusion:

knowledge of the expected risk factors for fistula after different protocols of palatoplasty can improve the experience of the surgeon and improve the outcome on the patients.

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Publication Date
Mon Jul 10 2023
Journal Name
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Theoretical Evaluation of Solar Assisted Desiccant Cooling System for a Small Meeting-Hall
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Publication Date
Fri Jan 01 2016
Journal Name
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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Publication Date
Sat Apr 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Channel state information estimation for reconfigurable intelligent surfaces based on received signal analysis
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Publication Date
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
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Pressure Gradient Influence on MHD Flow for Generalized Burgers’ Fluid with Slip Condition
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Sat Aug 02 2025
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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