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    The Association Between Sleep Quality, Fatigue and Periodontal Status: a Pilot Study
    (Univ Costa Rica, Fac Odontologia, 2023) Eroglu, Zeynep Tastan; Ozkan, Dilek; Yarkac, Fatma Ucan; Altiparmak, Fatma
    Reduced sleep duration, poor sleep quality and fatigue are related to reduced immunity and increased inflammatory markers. Due to its potential to influence inflammation, poor sleep quality and fatigue could be factors for periodontitis and quality of life. Ninety-three individuals with untreated periodontitis and thirty-one individuals with healthy gingiva were included in the study. The research involved a clinical examination and a questionnaire. Demographic information, information on oral health, oral hygiene habits, the Pittsburgh Sleep Quality Index, Jenkins Sleep Scale, Multidimensional Assessment of Fatigue Scale, and Oral Health Impact Profile-14 were included in the questionnaire. Patients were diagnosed based on the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. No statistically significant difference was revealed between sleep quality, fatigue, oral health related quality of life, and stage-grade of periodontitis (p<0.05). However, periodontitis group had higher Oral Health Impact Profile-14 scores (p<0.05). A statistically significantly lower sleep duration was observed in stage IV periodontitis group than the other groups (p<0.05). A statistically significant positive correlation was observed between the Pittsburgh Sleep Quality Index and the scores of the other questionnaires (p<0.05). The stage of periodontitis may impact sleep duration.
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    The Association Between Sleep Quality, Fatigue and Periodontal Status: a Pilot Study
    (Univ Costa Rica, Fac Odontologia, 2023) Eroglu, Zeynep Tastan; Ozkan, Dilek; Yarkac, Fatma Ucan; Altiparmak, Fatma
    Reduced sleep duration, poor sleep quality and fatigue are related to reduced immunity and increased inflammatory markers. Due to its potential to influence inflammation, poor sleep quality and fatigue could be factors for periodontitis and quality of life. Ninety-three individuals with untreated periodontitis and thirty-one individuals with healthy gingiva were included in the study. The research involved a clinical examination and a questionnaire. Demographic information, information on oral health, oral hygiene habits, the Pittsburgh Sleep Quality Index, Jenkins Sleep Scale, Multidimensional Assessment of Fatigue Scale, and Oral Health Impact Profile-14 were included in the questionnaire. Patients were diagnosed based on the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. No statistically significant difference was revealed between sleep quality, fatigue, oral health related quality of life, and stage-grade of periodontitis (p<0.05). However, periodontitis group had higher Oral Health Impact Profile-14 scores (p<0.05). A statistically significantly lower sleep duration was observed in stage IV periodontitis group than the other groups (p<0.05). A statistically significant positive correlation was observed between the Pittsburgh Sleep Quality Index and the scores of the other questionnaires (p<0.05). The stage of periodontitis may impact sleep duration.
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    Potential Use of ChatGPT for Patient Information in Periodontology: A Descriptive Pilot Study
    (Springernature, 2023) Babayigit, Osman; Eroglu, Zeynep Tastan; Sen, Dilek Ozkan; Yarkac, Fatma Ucan
    ObjectivesThe aim of this study is to evaluate the accuracy and completeness of the answers given by Chat Generative Pre-trained Transformer (ChatGPT) (OpenAI OpCo, LLC, San Francisco, CA), to the most frequently asked questions on different topics in the field of periodontology. MethodsThe 10 most frequently asked questions by patients about seven different topics (periodontal diseases, peri-implant diseases, tooth sensitivity, gingival recessions, halitosis, dental implants, and periodontal surgery) in periodontology were created by ChatGPT. To obtain responses, a set of 70 questions was submitted to ChatGPT, with an allocation of 10 questions per subject. The responses that were documented were assessed using two distinct Likert scales by professionals specializing in the subject of periodontology. The accuracy of the responses was rated on a Likert scale ranging from one to six, while the completeness of the responses was rated on a scale ranging from one to three. ResultsThe median accuracy score for all responses was six, while the completeness score was two. The mean scores for accuracy and completeness were 5.50 +/- 0.23 and 2.34 +/- 0.24, respectively. It was observed that ChatGPT's responses to the most frequently asked questions by patients for information purposes in periodontology were at least nearly completely correct in terms of accuracy and adequate in terms of completeness. There was a statistically significant difference between subjects in terms of accuracy and completeness (P<0.05). The highest and lowest accuracy scores were peri-implant diseases and gingival recession, respectively, while the highest and lowest completeness scores were gingival recession and dental implants, respectively. ConclusionsThe utilization of large language models has become increasingly prevalent, extending its applicability to patients within the healthcare domain. While ChatGPT may not offer absolute precision and comprehensive results without expert supervision, it is apparent that those within the field of periodontology can utilize it as an informational resource, albeit acknowledging the potential for inaccuracies.