Impact of Periodontal Disease on Quality of Life Among Periodontal Patients in Riyadh.

Kattan, ReemAl; Shibani, NoafAl; AlEnazi, Ghadah; AlNafa, Demah; Zahrani, HanadiAL

doi:10.21474/ijar01/6167

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Study carried out among 25 individuals in Saudi Arabia found that the impact of periodontitis on the patient’s QoL was statistically significant in two domains, namely psychological disability (P value 0.001) and physical pain (P value 0.004). The severity of periodontitis, in this current study, did not indicate a negative impact on functional limitation [ 26 ].…”

Section: Reviewmentioning

confidence: 77%

Impact of Oral Diseases and Conditions on Oral Health-Related Quality of Life: A Narrative Review of Studies Conducted in the Kingdom of Saudi Arabia

Mulla¹

2021

Cureus

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Oral health-related quality of life (OHRQoL) is a novel concept that has evolved over the past two decades. The World Health Organization (WHO) has also recognized it as a significant part of the Global Oral Health Program (2003). Information on OHRQoL gives better understanding about feelings and perceptions on an individual level. It also helps us to understand the impact of oral health on the lives on the patients and their family. It is now well documented that oral diseases and conditions impact people’s life. Some of the oral diseases/conditions like caries, dental fluorosis, tooth loss, periodontal disease, dental injuries, oral cancer, dental anomalies, craniofacial disorders, and many more have got negative impact on QoL. This paper identifies the various literatures published on the impact of oral diseases and conditions on OHRQoL in the population of Saudi Arabia. Although numerous researches can be found in other countries, the data on Saudi Arabian population are limited, leading to the need for carrying out more research in this area.

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Section: Reviewmentioning

confidence: 77%

Impact of Oral Diseases and Conditions on Oral Health-Related Quality of Life: A Narrative Review of Studies Conducted in the Kingdom of Saudi Arabia

Mulla¹

2021

Cureus

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“…A number of oral health factors have been linked with poor OHRQoL and this has been reported by several studies internationally [33,4,13,15,26] and a few from India [31,20]. However empirical evidence as to which factors are truly affecting OHRQoL is lacking.…”

Section: Introductionmentioning

confidence: 99%

Interpretable machine learning model for data driven classification of Oral Health Related Quality of Life in Patients with Type 2 Diabetes Mellitus

Srivastava,

Murali,

Jain

et al. 2024

Preprint

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Type 2 Diabetes Mellitus(T2DM) is a debilitating condition with a number of complications including those of the oral cavity which can further deteriorate patients general and oral health related quality of life (OHRQoL). Machine Learning (ML) can help assign an individuals propensity to develop poor OHRQoL, given a set of variables, and at the same time identify the most important features contributing to this outcome. Previously inferential statistical methods have attempted to explain this, albeit with limited success. The aim of this cross sectional study is to determine the impact on OHRQoL in T2DM patients, and identify features most likely to be associated with this outcome and to compare ML and DL analytical methods with inferential statistics. Twelve-hundred T2DM patients were subjected to OHRQoL and demographic data questionnaires and WHO Oral Health Assessment form. K-means Clustering was performed to label individuals as having or not having an impact on OHRQoL. Class imbalance was addressed by undersampling of the majority class using informed subset selection. Further, using the collected data as input features we developed ML algorithms (Naive Bayes(NB), Random Forest(RF), Logistic Regression(LR), Kernel Support Vector Machine(SVM) and Artificial Neural Network(ANN)), to accurately classify individuals with or without poor oral health related quality of life (OHRQoL) and utilized SHapley Additive exPlanations (SHAP) analysis for feature importance. The best performing model was SVM (AUC=0.983; Sensitivity=1) for classifying the patients into into poor OHRQoL. SHAP values were highest for Age, Prosthetic Need, Tobacco use and years since onset of diabetes. Features closely related to diabetes, that is, periodontal pockets and loss of attachment were not identified as relevant by inferential statistics, but were deemed as important features associated with poor OHRQoL by SHAP analysis.

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Knowledge and practice of mothers regarding use of Antibiotics and Antibiotic resistance

Paul

Alex

Varghese

et al. 2022

IJNER

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Antibiotic resistance is the ability of a microorganism to withstand the effects of an antibiotic. When bacteria become resistant, the powerful antibiotics can no longer fight them, and the bacteria multiply causing the disease to flare up leading to deaths. A report ‘Review Antimicrobial Resistance’, stated that the deaths attributable to antimicrobial resistance [AMR] every year compared to other major causes of death in 2050 will be 10 million, as compared to death by RTA’s, cancer, cholera, DM, measles and tetanus.1 But, with the help of proper health education, 90% of the antibiotic resistance can be reduced2. Children are a vulnerable group more prone for infections, and thereby are higher consumers of antibiotics. Since, mothers are the prime decision makers of their child’s health, the investigators felt the need to assess the “Knowledge and practice regarding the use of antibiotics and antibiotic resistance among the mothers of children in the paediatric wards at a selected hospital in Pathanamthitta”. 100 mothers were selected for the current study using convenient sampling technique. Baseline variables, knowledge and practice among the mothers were assessed by using baseline performa, structured knowledge and practice questionnaire. The knowledge and practice scores were analyzed using frequency, percentage, mean and standard deviation. The association of the scores with selected baseline variables were assessed using Chi-square test and Kruskal-Wallis test. And the correlations of the knowledge and practice scores were assessed using the Pearson’s coefficient of correlation. In this study among 100 mothers, 65(65%) of mothers were found to have good knowledge, 26(26%) mothers had poor knowledge and 9 (9%) are having excellent knowledge regarding antibiotics and antibiotic resistance. About 47(47%) of them were having best practice, 45(45%) were found to have good practice and 8(8%) had poor practice with respect to use of antibiotics for their children. No correlation was found between mothers’ knowledge regarding the antibiotics and antibiotic resistance and their practice. In view of the study results, a pamphlet was developed and given to the ward for distribution to the parents of children getting admitted in the wards after content validity and expert advice.

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Impact of Periodontal Disease on Quality of Life Among Periodontal Patients in Riyadh.

Cited by 4 publications

References 12 publications

Impact of Oral Diseases and Conditions on Oral Health-Related Quality of Life: A Narrative Review of Studies Conducted in the Kingdom of Saudi Arabia

Impact of Oral Diseases and Conditions on Oral Health-Related Quality of Life: A Narrative Review of Studies Conducted in the Kingdom of Saudi Arabia

Interpretable machine learning model for data driven classification of Oral Health Related Quality of Life in Patients with Type 2 Diabetes Mellitus

Knowledge and practice of mothers regarding use of Antibiotics and Antibiotic resistance

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