«EVALUATION OF ORAL NEUTROPHIL LEVELS AS A QUANTITATIVE MEASURE OF PERIODONTAL INFLAMMATORY LOAD IN PATIENTS WITH SPECIAL NEEDS By Anita Moosani BSc, ...»
EVALUATION OF ORAL NEUTROPHIL LEVELS
AS A QUANTITATIVE MEASURE OF PERIODONTAL
INFLAMMATORY LOAD IN PATIENTS WITH SPECIAL NEEDS
Anita Moosani BSc, DDS
A thesis submitted in conformity with the requirements
for the Degree of Masters of Science
Graduate Department of Paediatric Dentistry
Faculty of Dentistry
University of Toronto
© Copyright by Anita Moosani 2012 ABSTRACT Evaluation of Oral Neutrophil Levels as a Quantitative Measure of Periodontal Inflammatory Load in Patients with Special Needs Anita Moosani Masters of Science in Paediatric Dentistry, 2012 Department of Paediatric Dentistry, Faculty of Dentistry, University of Toronto Purpose: To validate and assess the feasibility of using an assay of oral neutrophils to measure periodontal inflammation in uncooperative patients with special needs.
Methods: Periodontal examination and neutrophil counts derived from oral swabs were performed on patients with special needs having comprehensive dental treatment under general anaesthesia (GA). The conventional periodontal measurements were compared to neutrophil levels while patients were under GA, and later at their recall examination.
Results: Forty-nine patients were assessed under GA and 30 (61%) returned for recall examination. Spearman‟s correlation allowed for comparisons between periodontal parameters and oral neutrophil counts. Despite limited cooperation, it was possible to acquire neutrophils (using swabs) for all patients that presented for recall examination in the ambulatory dental clinic.
Conclusions: Oral neutrophil levels correlated significantly with conventional parameters of gingival inflammation and may serve as a standardized method for clinical assessment of periodontal diseases in the special needs population.
ACKNOWLEDGEMENTSThis project was made possible by the kind and generous support of the following individuals.
Thank you to Dr. Michael Sigal for providing me with the opportunity to serve the special needs population as a hospital and graduate paediatric dental resident. Thank you for sharing your knowledge and dedication for a patient population that you have served so well. You have been a devoted teacher and inspiring mentor, and shown me what it means to be a caring paediatric dentist.
Thank you to Dr. Howard Tenenbaum for your constant encouragement and for sharing your enthusiasm for research with me. Your prompt response to emails from around the world and thorough editing of submissions was really appreciated. Thank you for a rich and memorable learning experience with my first research project.
Thank you to Dr. Michael Glogauer for a wonderful project that provides hope for improvement in periodontal diagnostics for at-risk populations. Your continual sense of calm and insightful perspective significantly contributed to the success of my research journey, and I sincerely appreciate all of the guidance you have given me.
Thank you to Dr. Michael Goldberg and Dr. Herenia Lawrence for being on my Masters committee, and for providing valuable feedback during the entire course of this research project.
Thank you to Dr. Mary-Ellen Cascone for introducing me to the special needs population.
Sharing your passion with me led me to the career path I am on today. Your compassion for your patients and love for teaching is contagious. Thank you for your guidance and friendship.
Thank you to Members of Dr. Glogauer‟s Laboratory, especially Ashkan Javid, for teaching me the laboratory techniques integral to this project, and assistance with data processing. Thank you to Matthew Sigal for your prompt input while preparing the study protocol and analyses.
Thank you to all of the Staff, Patients, and Families at The Mount Sinai Hospital Dental Clinic and Elective Outpatient Surgery (EOPS) Department for your help and participation.
Thank you to The Mount Sinai Hospital and U of T Paediatric Dental Residents, for helping with data collection, and for making the last three years so fun and memorable.
Thank you to all of my instructors in The U of T Undergraduate and Graduate Paediatric Dentistry Program, for sharing your knowledge and experience with me, and for being an invaluable part of my academic journey.
Most importantly, thank you to my parents for your unconditional love and support, and for providing me with the freedom, courage, and strength to pursue my goals. You have taught me by example the meaning of compassion, kindness, and humility. Your sacrifices, dedication, and encouragement are overwhelming and have contributed to all the successes I have been granted.
Words are powerless to express my gratitude and how truly blessed I am to have you in my life.
I am so lucky to have had you beside me in this journey, every step of the way. I love you!
High Prevalence of Gingival Inflammation in Patients with Special Needs 64 Positive Treatment Outcomes in Uncooperative Patients with Special Needs 65 Correlation of Periodontal and Neutrophil Variables for Assessments under GA 66 Correlation of Periodontal and Neutrophil Variables for Assessments at Recall 67 Severity of Developmental Delay Influences Gingival Inflammation 68 Acquisition of Oral Swab Data is Feasible 69 Correlation of the VAS with Traditional Periodontal Measures & PMN Counts 69
Figure 1: Severity of Developmental Delay in Patients Assessed under GA (n = 49) and at Recall Examination (n = 30) Figure 2: Frankl Behaviour Rating Score in Patients Assessed Prior to GA (n = 49) and at Recall Examination (n = 30) Figure 3: Prevalence of Gingival Inflammatory Diseases in Patients Assessed under GA (n = 49) Figure 4: Time Elapsed (in months) Between GA and Recall Appointments (n = 30) Figure 5: Relationship Between Severity of Developmental Delay and Frankl Behaviour Rating Score Prior to GA Assessment (n = 49)
Table 1: Intra-Class Correlation Coefficients (ICC) for Intra-Calibration Analyses of Examiners 1 to 7 and Gold Standard (GS) Table 2: Intra-Class Correlation Coefficients (ICC) for Inter-Calibration Analyses of Participants 1 to 6 and Gold Standard (GS), at Sessions 1 and 2 Table 3: Descriptive Characteristics for Residents Assessed at Calibration Sessions with the PMN Assay (n = 9) Table 4: Patient Flow During Recruitment and Reasons for Exclusion from this Study Table 5: Descriptive Characteristics for Patients Assessed under GA (n = 49) and at Recall (n = 30) Table 6: Concurrent Medical Diagnoses of Patients Assessed in this Study in Order of Frequency (n = 49) Table 7: Daily Medications Taken by Patients Assessed in this Study According to Drug Category and in Order of Frequency (n = 49) Table 8: Reasons for Loss to Follow-Up Table 9: Spearman Correlation Coefficients (rs) and p Values Comparing Periodontal Measures and Total Neutrophils for Assessments under GA (n = 49) Table 10: Spearman Correlation Coefficients (rs) and p Values Comparing Periodontal Measures and Total Neutrophils Controlling for Number of Teeth for Assessments under GA (n = 49) Table 11: Spearman Correlation Coefficients (rs) and p Values Comparing Periodontal Measures and Total Neutrophils Controlling for Number of Teeth for Assessments at Recall (n = 27) Table 12: Mean ± Standard Deviations and Wilcoxon Signed Ranks Test to Compare Mean Periodontal Measures Assessed under GA (n = 49, n = 30) and at Recall (n = 30) Table 13: Mean and Standard Error of Neutrophil Counts Obtained at Recall, Distinguished by Severity of Developmental Delay, and Controlling for Age and Baseline Levels of Neutrophil Counts under GA Table 14: Analysis of Covariance (ANCOVA) Model for Neutrophil Counts Obtained at Recall, Controlling for Baseline Levels of Neutrophil Counts under GA Table 15: Analysis of Covariance (ANCOVA) Model for the Difference in Neutrophil Counts Obtained at GA and Recall Table 16: Spearman Correlation Coefficients (rs) and p Values Comparing Periodontal Measures and Total Neutrophils Controlling for Number of Teeth with VAS for Gingival Inflammation, for Assessments at GA (n = 49) and Recall (n = 30)
1. Frankl Behaviour Rating Scale for Assessment of Cooperation in the Dental Clinic
2. Research Invitation Letter and Consent Form
3. Overview of Study Patient Flow and Evaluators
4. Definitions of Periodontal Measures of Gingival Inflammation Used in this Study
2, 2‟ – azinobis (3-ethylbenzothiazoline-6-sulphonic acid)
ANCOVA: Analysis of covariance BOB: Bleeding on brushing BOP: Bleeding on probing CAL: Clinical attachment loss
MGI: Modified gingival index MMP: Matrix metalloproteinase MPO: Myeloperoxidase NADPH: Nicotinamide adenine dinucleotide phosphate oxidase OMR: Orogranulocytic migratory rate
PMN: Polymorphonuclear leukocyte or neutrophil PMNs: Polymorphonuclear leukocytes or neutrophils rs: Spearman correlation coefficient TNFa: Tumor necrosis factor alpha VAS: Visual analog scale
Patients with special needs have a high prevalence of oral disease (Scott, March, & Stokes, 1998; Lopez del Valle, Waldman, & Perlman, 2007; Dellavia, Allievi, Pallavera, Rosati, & Sforza, 2009; Anders & Davis, 2010), which can be difficult to diagnose with the conventional instruments that are used to detect disease in the dental office, where a periodontal examination may be impossible due to lack of patient cooperation. Literature to propose or support the use of alternative strategies for diagnosis of gingival or periodontal health status in the special needs population is lacking (Hennequin, Faulks, & Roux, 2000).
The lack of appropriate diagnoses of gingival and periodontal diseases prevents the delivery of optimal treatment. Therefore, periodontal problems could go undetected and untreated.
This is especially relevant when recognizing oral health as an important component of general health and well-being (Boehm & Scannapieco, 2007; Brennan, Spencer, & RobertsThomson, 2007), and the increased potential risk of pulmonary infections in special needs patients with poor oral hygiene (Scannapieco, 1999; Scannapieco, 2005b; Scannapieco, 2006; Sigal & Sigal, 2006).
Periodontal diseases are a group of inflammatory disorders characterized by progressive destruction of the periodontium, specifically the tissues surrounding and supporting the teeth (Armitage, 1999). The destruction of tissue observed in the presence of periodontitis is a consequence of an interaction between the host inflammatory response and pathogenic bacteria within the periodontal crevicular space (Deas, Mackey, & McDonnell, 2003; Van Dyke, 2008; Sanz & van Winkelhoff, 2011). This excessive inflammation leads to a disruption of the normally homeostatic relationship between bone and periodontal ligament formation and breakdown - in favour of breakdown. Once this homeostatic relationship is altered as noted above, the eventual result is that of loss of tissues supporting the teeth, and ultimately, loss of teeth. Disease susceptibility, progression, severity, and response to treatment are mostly determined by host-based factors (Kinane, Peterson, & Stathopoulou, 2006). Periodontal disease significantly increases the risk of tooth loss resulting in loss of masticatory function, malnutrition that affects general health, and an overall decrease in quality of life (Boehm & Scannapieco, 2007; Brennan, Spencer, & Roberts-Thomson, 2007).
Clinical parameters that are currently used for the assessment of gingival health status include: erythema, swelling or enlargement of gingival contours due to edema or soft tissue hyperplasia, plaque and calculus accumulation, periodontal probing depths, bleeding on probing, clinical attachment loss, gingival recession, furcation involvement, tooth mobility, and radiographic alveolar bone loss (Haffajee, Socransky, & Goodson, 1983; Mariotti, 1999;
Pihlstrom, 2001). Though considered to be the gold standard in periodontal disease diagnosis, these parameters are noted to have numerous limitations, the most important being the fact that these measures do not necessarily indicate whether a patient with periodontitis has active or inactive disease (i.e. will the disease continue to progress without treatment;
Haffajee et al., 1991; Armitage, 1996). Acknowledging the limitations of the currently used clinical measures of periodontal health status emphasizes the necessity for pursuit of other and better diagnostics for periodontal disease (Apsey, Kaciroti, & Loesche, 2006).
Polymorphonuclear leukocytes (PMNs) or neutrophils, are a major cellular element of the innate immune system (Lavelle, 1992; Hart, Shapira, & Van Dyke, 1994), and are vital for the host‟s immune response to virulent bacteria (Van Dyke & Hoop, 1990). Neutrophils play a major role in the host response to invading periodontal pathogens (Hart, Shapira, & Van Dyke, 1994), and the gingival sulcus is the major site of entry of leukocytes into the oral cavity (Sharry & Krasse, 1960). The PMN is able to detect infection, migrate to the site of disease, destroy pathogens, and influence bacterial growth and colonization in periodontal tissues (Deas, Mackey, & McDonnell, 2003). Neutrophils have been shown to increase in quantity in proportion to gingival inflammation (Attstrom, 1970; Schroeder, 1973), and the protection conferred by the host response effectively defends against the bacterial insults that constantly threaten the health status of the periodontium in the majority of the population (Deas, Mackey, & McDonnell, 2003; Schenkein, 2006). However, the protection provided by the PMN is not without consequence. The PMN‟s bactericidal or killing mechanisms also have the potential to damage extracellular tissues via the release of granular constituents containing degradative enzymes called matrix metalloproteinases (MMP), for example, MMP-8, also known as collagenase, myeloperoxidases (MPO), and reactive oxygen species (Van Dyke & Hoop, 1990; Lamster, 1992; Deas, Mackey, & McDonnell, 2003).