«EVALUATION OF ORAL NEUTROPHIL LEVELS AS A QUANTITATIVE MEASURE OF PERIODONTAL INFLAMMATORY LOAD IN PATIENTS WITH SPECIAL NEEDS By Anita Moosani BSc, ...»
Clinical Indices Clinical parameters that are currently used for the assessment of gingival health status include: erythema, edema due to swelling itself or possibly due to hyperplasia of underlying connective tissues, accumulation of bacterial plaque and calculus, increased probing depths (i.e. above any beyond the probing depths accepted as representing normalcy; 0-3 mm), bleeding on probing, clinical attachment loss, gingival recession, furcation involvement, tooth mobility, and radiographic evidence for loss of alveolar bone (Haffajee, Socransky, & Goodson, 1983; Mariotti, 1999; Pihlstrom, 2001). However, these parameters have also been noted to have numerous limitations, in that they only provide measures of past disease activity, and cannot be used to determine current disease activity or to prognosticate as to progression of disease and tissue destruction in the future (Haffajee et al., 1991; Armitage, 1996).
Numerous indexing systems have been created to grade the severity and extent of gingival and periodontal diseases, in order to translate the above clinical findings into numerically scaled quantities. Indices such as the periodontal disease index (Ramfjord, 1959), and the oral hygiene index (Greene & Vermillion, 1964), were developed to serve as tools for rapid screening of large populations for periodontal disease (Ainamo & Bay, 1975). This has allowed for determination of the prevalence of gingival diseases in large populations, as well as evaluation of treatment outcomes. Specific teeth or the entire dentition are measured at 4 or 6 sites and may then be averaged to specify the mean score for the entire mouth. Thus, the indices provide semi-quantitative information about disease severity and can be analyzed statistically (Ramfjord, 1959). Unfortunately, when it comes to the analysis of discontinuous or non-parametric scales, the use of mean data may not allow for robust statistical analysis.
The pitfall in using mean individual scores is that the implication of disease when relating scores from 0 to 1 compared to 1 to 2 are not equivalent (Ainamo & Bay, 1975).
Furthermore, an ordinal score of „3‟ is not three times worse than an ordinal score of „1‟, which further underscores the inappropriateness of using mean data when applying the various indices for assessment and quantification of periodontal diseases. Moreover, there is a degree of subjectivity involved in the use of periodontal disease indices including the presence of measurement error due to inter- and intra-examiner differences (Haffajee et al., 1991; Lamster, Celenti, Jans, Fine, & Grbic, 1993; Pihlstrom, 2001). It is also noteworthy that different categories within the different indices are divided and detailed in order to be more sensitive to variation, but can result in problems with examiner reliability, where the examiner has difficulty in assigning a score – and assigning the score consistently – when there are more categories available (Greene, 1967; Benamghar, Penaud, Kaminsky, Abt, & Martin, 1982; Kingman, Löe, Anerud, & Boysen, 1991). Finally, these scales lack the specificity and objectivity needed for evaluation of an individual patient‟s disease status (Klinkhamer, 1968).
Limitations in Diagnosis of Periodontal Diseases Diagnosis of gingival inflammation in the clinical setting is limited to traditional methods of assessing disease that have now been described. Conventional measures of periodontal disease can be divided into two main approaches: those used to assess severity of disease, or those concerned with activity of disease. Severity of disease can be defined as the periodontal health status at the time of examination, and is measured using the various measures noted above. In contrast, measurement of disease activity (e.g. progression of periodontal attachment loss), is more difficult as it relies on changes in the clinical parameters used to assess periodontal disease over a specific period of time (Lamster, Celenti, Jans, Fine, & Grbic, 1993); parameters which themselves are open to significant variation and in and of themselves, given a particular single time of assessment, do not necessarily convey whether disease is active or not. In this regard, disease activity is measured once damage to the periodontium has already occurred (e.g. progressive attachment loss; Lang, Joss, Orsanic, Gusberti, & Siegrist, 1986). This type of measurement cannot be used for reliable prognostication of future disease activity. Diagnosis is complicated further by studies showing that periodontal diseases do not appear to follow a linear pattern of progression, but rather are characterized by periods of latency and exacerbations (Goodson, Tanner, Haffajee, & Sornberger, Socransky, 1982; Socransky, Haffajee, Goodson, & Lindhe, 1984). Therefore, even in cases where severe destruction of tissue has been demonstrated, this information cannot be used unequivocally to predict that future disease progression will ensue. Indeed, it has been shown in an assessment of the clinical parameters for periodontitis that are currently used in dental practice, that none were useful in predicting disease activity at individual sites when used either individually or in combination (Haffajee, Socransky, & Goodson, 1983).
Limitations of Diagnosis in the Special Needs Population The measurement of the above clinical parameters in the uncooperative special needs population with accuracy, efficiency, and safety is a challenge. In addition to the problems associated with measurement of periodontal disease severity and activity in otherwise cooperative patients, it cannot be overstated that most methods of measurement in the uncooperative special needs population are even more difficult and in some cases virtually impossible. Studies that attempt to assess the oral health status of patients with disabilities are unable to compare the periodontal conditions adequately due to difficulties in acquiring periodontal indices or measures that require patient cooperation, which could actually be traumatic if attempted. Therefore, any measurements made are suspect insofar as accuracy is concerned. In this regard, a conventional periodontal examination with visual inspection and a periodontal probe may be impossible due to lack of patient cooperation (Hennequin, Faulks, & Roux, 2000). This means that we not only have little information regarding the true periodontal status of such patients (until they are placed under a general anaesthetic), but any efforts to develop novel and more user-friendly treatments for patients in this population are substantially hampered due to the inability to follow the progression or regression of periodontitis without placing such patients under a general anaesthetic more often than would be appropriate from a clinical and ethical standpoint. Unfortunately, literature to propose or support the use of alternative strategies that could be used for diagnosis of gingival or periodontal health status in the special needs population is lacking. In fact, oral health needs are often underestimated by caregivers and dental health professionals due to the patients‟ inability to express pain or discomfort, and an inability to obtain reliable clinical data using any number of diagnostic tests that, in a cooperative population could be done, but cannot be done in the uncooperative population of special needs patients (e.g. vitality testing, periodontal probing). As already stated above, the limitations in diagnostic tests available to assess the periodontal status of the uncooperative special needs patient in a non-invasive manner precludes accurate diagnosis and prognostication. Therefore, it is also not possible to formulate individualized and appropriate treatment plans designed to place such patients in a position of optimal oral health, or to monitor the outcomes of treatment accurately.
The Visual Analog Scale as a Measure of Gingival Inflammation The Visual Analog Scale (VAS) is a measurement that is often used for the subjective assessment of dental pain (Seymour, Charlton, & Phillips, 1983), and has also been noted as an effective means of evaluation for patient perceptions of post-operative variables after periodontal treatment (Matthews & McCulloch, 1993). Notably, its application has been suggested for use by the patient as a quantitative yet subjective indicator in order to guide the clinicians‟ assessment. However, the literature does not include the VAS as a periodontal measure for inflammation, and indices such as the gingival bleeding index (Ainamo & Bay, 1975), rather than the VAS, are traditionally used during periodontal examination as discussed earlier. In the uncooperative special needs population, the time available for patient assessment is limited due to the potential for rapid deterioration of behaviour with longer appointment times. In this case, measurement of various indices that involve placing the clinical picture within multiple categories by the examiner can be time-consuming and impractical. Thus, the current assessment of periodontal health in this population often involves an overall impression or use of a VAS, regarding severity and prognosis of periodontal disease and consequent treatment needs.
Novel Methods for Assessment of Periodontal Disease Activity An understanding of the limitations of the currently used clinical measures of periodontal health status seriously underscores the necessity for pursuit of other and better diagnostics for periodontal disease (Apsey, Kaciroti, & Loesche, 2006). Ideally, a clinical parameter could be used to monitor periodontal destruction in three ways. It could record active disease, allow for quantitative monitoring of treatment responses, and indicate susceptibility to disease (Fine & Mandel, 1986). Diagnostic tests for periodontal disease are useful in patients that have not received periodontal therapy, providing a baseline measure of disease status.
Following periodontal treatment, diagnostic tests may demonstrate responses to treatment and identify disease progression and future risk of disease, which is directly helpful in the clinical situation in directing subsequent treatment, including determination of need and extent of future treatment (Lamster, Celenti, Jans, Fine, & Grbic, 1993).
In light of the limitations noted with the current methods used for the diagnosis and assessment of periodontal disease severity, there have been efforts to develop diagnostic tests that are based on evaluation of factors that are thought to play an important role in the pathogenesis of periodontal diseases, with emphasis not only on its presence or severity, but also the activity of the disease once identified. Wherever possible the goals have been to develop diagnostic tools that are as objective and quantitative as possible which would allow for the identification of the different presentations of periodontal disease, measurement of disease activity and progression, while also allowing for the prediction of future disease activity (Fine & Mandel, 1986; Cao & Smith, 1989; Lamster, Celenti, Jans, Fine, & Grbic, 1993; Ranney, 1993). Current supplemental diagnostic tests are focused on different aspects of the disease that have been identified to play important roles in the pathophysiological processes of periodontitis including: detection of microbial periodontal pathogens, assessment of host-derived enzymes that might degrade periodontal tissues, identification of breakdown products from diseased periodontium, mediators of inflammation, and genetic testing (the latter predominantly for assessment of disease-risk). Although these tests have provided valuable information, they cannot be applied readily to the clinical setting as they require increased clinical time to be performed, while they also require specialized equipment and training to be used properly (Fine & Mandel, 1986; Landzberg, Yuen, & Glogauer, 2008).
Gingival Crevicular Fluid – Insights and Limitations Investigation of the constituents of gingival crevicular fluid (GCF) has been an active area of research focusing on the pathophysiology of periodontal disease. Constituents of GCF are derived from many sources, including substances from the host as well as from the microorganisms inhabiting the subgingival biofilm. The contents of GCF mirror the makeup of serum (being in large part a serum transudate), while GCF also contains the cytokines and products of periodontal metabolism noted above (as inflammatory exudate; Lamster & Ahlo, 2007). More than 65 components of GCF have been tested as potential diagnostic markers for periodontal disease progression, and have been grouped into three categories: 1) hostderived enzymes and their inhibitors, 2) inflammatory mediators and host-response modifiers, and 3) byproducts of tissue breakdown (Armitage, 2004). In understanding the constituents of GCF it has been hoped that changes in any one of its several components might be used to demonstrate the presence, severity, progression or likelihood of progression of periodontal disease in a given area.
Analysis of GCF seems to have the potential to contribute to the development of valuable diagnostic tests, but its application is still limited in the dental practice setting. With respect to ease of use, it is a relatively simple task to collect GCF from the gingival sulcus surrounding the teeth for later assessment. Saliva can be collected non-invasively by persons who have limited training, and special equipment for collection of saliva is typically not required. Saliva collection is also well tolerated by patients and may be cost-effective when screening large populations (Kaufman & Lamster, 2002). However, collection of GCF requires some time and multiple samples are often taken from each patient. Also, selection of the tooth or teeth to be used for collection of GCF can be subjective or random meaning that identification of sites that are at-risk for further breakdown, or are at the very least „diseased‟ can be difficult (Lamster & Ahlo, 2007). Clinicians may also lack comfort with using some of the diagnostic tests currently under development, particularly when the tests might be used for the assessment of health status and formulation of ongoing treatment plans.