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  1. Liew AK, Abdullah D, Wan Noorina WA, Khoo S
    Dent Traumatol, 2014 Dec;30(6):461-7.
    PMID: 24890132 DOI: 10.1111/edt.12114
    To assess rugby players' preferences for using a mouthguard and to determine the factors contributing to the use and discontinuation of a mouthguard.
  2. Abdullah D, Syed Mohamed AMF, Cheen Liew AK
    J Conserv Dent, 2019 3 2;22(1):102-106.
    PMID: 30820092 DOI: 10.4103/JCD.JCD_113_18
    Although corticosteroid provides many clinical benefits, it may cause a range of side effects. A 47-year-old female patient presented with a complaint of pain from her teeth, triggered upon taking cold, hot, and sweet food and drink. From her medical history, she was previously diagnosed with ulcerative colitis. She consequently developed pyoderma gangrenosum, and high-dose prednisolone was administered to treat this condition (prednisolone 30 mg bd for 4 months followed by tapering dose 5 mg/week). She claimed the pain started at the end of steroid therapy. The pain mimicked symptoms of dentine hypersensitivity, but without the presence of the clinical signs associated with hypersensitivity, suggesting that the pain was steroid induced. Patients in this condition will find that their dietary choices will be limited and effective oral hygiene be impeded. Reassurance and advising patients to maintain oral hygiene are the most appropriate treatment as this condition would eventually wear off with time.
  3. Abdullah D, Liew AK, Wan Noorina WA, Khoo S, Wee FC
    Dent Traumatol, 2015 Oct;31(5):403-8.
    PMID: 26058666 DOI: 10.1111/edt.12191
    OBJECTIVES: To assess and compare the knowledge of rugby players regarding first-aid measures for dental injuries.

    METHODS: A cross-sectional study was conducted at rugby tournaments in 2009 and 2010 on players aged 16 and over. Convenient sampling was performed. A total of 456 self-administered questionnaires were returned. Data collected were analysed using SPSS 21. Descriptive analysis was undertaken for the demographic data. The subjects were classified according to their experience of sustaining each type of injury. Cross-tabulation and chi-square tests were carried out to compare the responses. When the expected cell count was less than five, Fisher's exact test was used. The level of significance was set at P < 0.05.

    RESULTS: The prevalence of self-reported dental injuries was as follows: tooth fracture (19.3%), luxation (6.6%) and avulsion (1.1%). Significant differences were found, whereby 52.2% of those who had no history of tooth fracture were more likely to seek immediate treatment (P < 0.001), whereas 42% of those who previously experienced tooth fracture claimed that they would only visit a dentist if they experienced pain (P = 0.001). Management of luxation and avulsion did not differ significantly between the groups. However, about half of those who did not have a history of tooth avulsion admitted to not knowing the correct answer, while three of five casualties would keep the tooth iced.

    CONCLUSIONS: Knowledge of the management of tooth fracture and storage medium differs between previous casualties and non-casualties. Overall, knowledge of dental trauma management was insufficient, suggesting the need to educate and train the players.

  4. Hussein FE, Liew AK, Ramlee RA, Abdullah D, Chong BS
    J Endod, 2016 Oct;42(10):1441-5.
    PMID: 27552839 DOI: 10.1016/j.joen.2016.07.009
    INTRODUCTION: Ignoring the cluster effect is a common statistical oversight that is also observed in endodontic research. The aim of this study was to explore the use of multilevel modeling in investigating the effect of tooth-level and patient-level factors on apical periodontitis (AP).

    METHODS: A random sample of digital panoramic radiographs from the database of a dental hospital was evaluated. Two calibrated examiners (κ ≥ 0.89) assessed the technical quality of the root fillings and the radiographic periapical health status by using the periapical index. Descriptive statistical analysis was carried out, followed by multilevel modeling by using tooth-level and patient-level predictors. Model fit information was obtained, and the findings of the best-fit model were reported.

    RESULTS: A total of 6409 teeth were included in the analysis. The predicted probability of a tooth having AP was 0.42%. There was a statistically significant variability between patients (P 

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