ASSESSMENT OF periodontal risk factors and indicators.pptx

7/27/2019 ASSESSMENT OF periodontal risk factors and indicators.pptx

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INTRODUCTION

As our understanding of periodontal diseases has deepened, it

has become clear that certain risk factors are associated with

disease development.

As dental professionals seek to optimize treatment and improve

outcomes for patients, the role of risk assessment and disease

management has become increasingly important.


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RISK ASSESSMENT..

According to MeSH, risk assessment can be defined as the

Qualitative or quantitative estimation of the likelihood of

adverse effects that may result from exposure to specifiedhealth hazards or from the absence of beneficial influences.

Risk assessment involves dental care providers, identifying

patients, and populations at increased risk of developingperiodontal disease.

The assessment of patients risk to controlsignificant impact

on clinical decision making.


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Rather than concentrating on obvious pathology that requires

immediate (and typically surgical) intervention, the risk

assessment model invites dental care professionals to take a

step back and look at the potential development of dentaldisease over the long term.

To improve clinical decision making, risk assessment can

reduce the need for complex periodontal therapy, improvepatient outcomes and ultimately reduce oral health care costs.


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This presentation reviews the application of risk assessment

and disease management to the general population and to

groups at risk of developing periodontal disease.


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RISK FACTORS

A risk factor can be defined as any environmental, behavioral,

or biologic factor that, when present, increases the likelihoodthat an individual will develop the disease.

Risk factorswith a disease but..cause the disease.

However, to be identified as a risk factor, the exposure must

occur before disease onset.


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Risk factors may be modifiable or non-modifiable.

Modifiable risk factors are usually environmental or behavioralin nature whereas non-modifiable risk factors are usually

intrinsic to the individual and therefore not easily changed.

Non-modifiable risk factors are also known as determinants.


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Associations identified through longitudinal and interventional

studies are termed risk factors whereas associations, based on

the observations of cross-sectional and case controlled studies

are termed risk indicators.

Thus the term risk factor denotes a greater weight of evidence

supporting an association than does the term risk indicator.


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CRITERIA FOR CAUSAL RELATION ACCEPTANCE

Causal inference, i.e. the procedure of drawing conclusions

related to the cause of disease is a complex issue.

In the 1970s, Hill (1971) formalized the criteria that have to befulfilled in order to accept a causal relation. These included:

Strength of association

Dose-response effect

Temporal consistency

Consistency of the findings

Biological plausibility

Specificity of the association


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1. Strength of association:

- Stronger the association between the potential risk factor and

disease, the more likely it is that the anticipated causal relationis valid.

2. Dose-response effect:

- An observation that the frequency of the disease increases with

the dose or level of exposure to a certain factor supports a causal

interpretation.


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3. Temporal consistency:

- It is important to establish that the exposure to the anticipated

causative factor occurred prior to the onset of the disease.- This may be difficult in case of diseases with long latent periods

or factors that change over time.

4. Consistency of the findings:

- If several studies investigating a given relationship generate

similar results, the causal interpretation is strengthened.


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5. Biological Plausibility:

- It is advantageous if the anticipated relationship makes sense

in the context of current biological knowledge.- Less that is known about the etiology of given disease, more

difficult it become to satisfy this criterion.

6. Specificity of the association:

- If the disease is found to be associated with only one factor

among a multitude of factors tested, the causal relationship is

strengthened.


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- it is important that the criteria described are meant as

guidelines when a causal inference is established.

- None of them, however, is either necessary or sufficient for acausal interpretation.

- Strict adherence to any of them without concomitant

consideration, may result in incorrect conclusions.


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PRINCIPLES OF RISK ASSESSMENT PROCESS

According to BECK (1994): STEPS:

Identification of factors to be associated with the disease.

In case of multiple factors, Multivariate risk assessment model

must be developed that discloses which combination of factors

does most effectively discriminate between health and disease.

Assessment: new populations are screened for this

combination of factors.

Targeting: exposure to the identified factors is modified by

prevention or intervention and the effectiveness of the approach

in suppressing the incidence of the disease is evaluated


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Thus, according to this process,potentialorputative risk factors

are first identified and thereafter tested until their significance

as true risk factoris proven.


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PERIODONTAL RISK FACTORS

According to Borrell and Papanou (2005):

- Non amenable to intervention ( non modifiable background

factors)

- Modifiable factors (environmental, acquired andbehavioral)


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NON MODIFIABLE BACKGROUND FACTORS

AGE:

Aging.increased incidence..

- Studies on periodontal disease prevalence, extent, and severity

show more disease in older age groups compared with younger

groups.

- However it has been suggested that the increased level of

periodontal destruction observed with aging is the result of

cumulative destruction rather than a result of increased rates of

destruction, thus aging is not a risk factorper se.


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GENDER:

Periodontal disease.. men at comparable ages.

Diseases related to attachment loss and bone height are more

common.

- Men exhibit poor oral hygiene and report fewer visits to the

dentist, than women.

- Female estrogen hormone protect against destructive

periodontal bone loss.


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RACE:

Assessment related to race, socio-economic status (SES) and

poverty have been unsuccessful in making associations with

periodontal disease.

Race/ ethnicity is a social construct that determines an array of

opportunities related to access, status and resources. As a

result,

- Race and SES are strongly intertwined, suggesting that the

racial effect may partially attributed to confounding by SES due

to the unequal meaning of SES indicators across racial groups.


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In a study of risk indicators for African Americans and

Caucasian Americans, there were more indicators related to

socioeconomic status.

- For e.g. Prevotella intermedia was a risk indicator for African

Americans but not for Caucasian Americans. But when

persons from both races belong to the same socioeconomic

group, differences in periodontal disease disappeared.


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GENETIC FACTORS: affect most oral conditions.

a. Genetic aspects of localized Juvenile Periodontal disease:

- LJP has a familial aggregation and has been thought to be agenetically determined condition.

- According to Long, Beaty, Hart , Saxby; periodontitis is a

because of autosomal mode of inheritance (transmission).

- According to some studies, genetic abnormalities in neutrophil

function may also associatebecause in LJP, the nuetrophil

functions are associated with genetic polymorphisms.


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Attempts to associate human leukocyte antigens (HLA) with JP

are conflicting.

- Reinholdt and colleagues.LJP patients have higher

prevalence of HLA-AG, HLA-A28, HLA-BW15.


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b. Genetic aspects of adult periodontitis:

Three approaches have been carried out,

- Human leukocyte antigen associations

- Twin studies,

- Genetic polymorphisms


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i. Human leukocyte antigen association:

- Early studies negative association of periodontitis with HLA-A2.

- Klouda, Amer and colleagues showed: increase in HLA-Ag in

patients with periodontitis, which was related to report

presented by Reinholdt for JP.


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ii. Twin studies:

- Carried out on 26 sets of twins aged 12-17 years, 7 pairs:

monozygotic and 19: dizygotic.

- No differences in gingival recession, gingival crevice depth,

gingival bleeding, calculus or plaque.

- Michalowicz and colleagues: alveolar bone was significantly

affected by genetic factors.

- The same group found: genetic influence on gingivitis, probing

depth, attachment loss and plaque.


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- These studies are provocative, leading to hypothesis relating to

genetic factors in periodontal disease.

- However, data must be reviewed cautiously,

- Changes in alveolar bone height may be genetic due to

anatomic variation and may or may not be related to

periodontal diseaseper se.


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iii. Genetic Polymorphisms:

- Are associated with adult periodontitis.

- For e.g. Kornman studied genetic polymorphisms in Pro-

inflammatory Cytokines IL-1. AND TN F-.

- This genotype was only responsible for PD in non smokers and

not in smokers.


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Van Schie and colleagues: relation between polymorphism

pattern & periodontitis.

Hence, it appears that candidate gene polymorphisms are a

useful approach in assessing genetic factors in both JP & AP.


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Pregnancy:

Periodontal disease has been shown to be associated with

preterm delivery and low birth weight`.

A recent study found a significant association between preterm

birth and third-molar periodontal disease in pregnant women.

Analysis of gingival crevicular fluid has demonstratedsignificantly higher levels of the inflammatory mediator

prostaglandin E2 in women who delivered preterm low-birth-

weight infants.


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However, other research has failed to demonstrate a link

between preterm low-birth-weight babies and periodontal

disease.

Although a causal connection has not been established, it is

appropriate to advise expectant mothers about the importance

of good oral health, including the use of antimicrobial rinses to

mitigate the impact of pathogenic bacteria.


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MODIFIABLE [ENVIRONMENTAL, ACQUIRED & BEHAVIORAL]

Periodontal Microflora:

- There are over 400 genera and species of micro-organisms.

- Three mainly implicated as etiogenic agents:

i. Porphyromans gingivalis,

ii. Tannerella forsythia (Bacteroides forsythus) and

iii. Actinobacillus actinomycetemcomitans.


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P. gingivalis and P. intermedia: PD in older adults.

P. gingivalis and B. forsythus: increased risk for attachment loss

and alveolar bone loss.

Presence of pathogens to is not sufficient.


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The odds ratio of developing periodontal disease in an

individual who harbors one of the putative perio. Pathognes is

not high enough to consider them a risk factor.

Presence of A. actinomycetemcomitans confrs no additional

risk of developing LAP, despite it is necessary for the disease to

develop.

It has been shown that P. intermedia, P. gingivalis and

Fusobacterium nucleatum may be risk indicators for periodontal

disease in a diverse population, though they are not riskfactors.


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Socio- economic status (SES):

- Gingivitis and poor oral hygiene can be related to lower SES.

- This can be attributed to decreased dental awareness and

decrease frequency of dental visits compared with more

educated individuals of higher SES.

- Lower SES alone does not result in increased risk for

periodontitis has to be adjusted with other risk factors, such

as smoking and poor oral hygiene.


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Stress & psychological factors:

- The incidence of NUG increases in emotional and physiologic

stress.

- Emotional stress may interfere with normal immune function

and may result in increased levels of circulating hormones

which can affect the periodontium.

- Association between psychological factors and risk behaviors (

smoking, poor oral hygiene)chronic periodontitis.


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Individuals with stress are more likely to develop clinical

attachment loss and loss of alveolar bone.

This may be due to link between stress and increase in

production of IL-6

Also the host response to P. gingivalis infection may becompromised in psychologically stressed individuals.


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Despite existing evidence from case control and cross sectional

studies, no longitudinal or interventional studies have been

published that confirm psychological stress as a risk factor forP.D.

Perhaps the relationship is due to the fact that individuals under

stress are less likely to perform regular good oral hygiene andprophylaxis.


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Tobacco Smoking:

The history of association investigated in the middle of the

last century.

Recently, many epidemiological, clinical and in vitro studies

have proven that smoking negatively impacts periodontal

health.

The incidence of CAL and ABL increases with increasedsmoking

- Heat from smoke may enhance attachment loss, and the

increased calculus deposits that often result from smoking can

enhance plaque retention.

- Nicotine can diminish collagen synthesis, protein secretion and

may inhibit bone formation.


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Former smokers (clinically 5 or more years since quitting),

experience less AL than current smokers and more than never

smokers.

The likelihood of developing periodontal disease exhibits dose

dependency.

Odds ratio for developing perio. disease:

- Current heavy smokers: 7.2

- Current light smokers: 3.2

- Former smokers: 1.6

Smoking is associated with reduced gingival bleeding.


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Smoking is associated with reduced gingival bleeding.

Smokers may experience less gingival bleeding than non

smokers.

It is suggested that,alterations of the caliber of the blood

vessels perfusing the gingival tissues.

These findings suggest.. a reduced reliance on the use of

gingival bleeding as an indicator of gingival inflammation when

assessing a smokers periodontal health.


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Some in vitro studies have shown altered gingival crevicular

fluid, inflammatory cytokine profiles, immune cell function and

altered proteolytic regulation in smokers.

Also majority of the periodontal treatments are less successful

in smokers.

Nonetheless, the results of these studies are inconsistent and

no clear mechanism has emerged to explain how smoking may

affect periodontal disease.

Smoking and genetic polymorphisms is the new area ofresearch


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Diabetes Mellitus:

- It is modifiable factorthough it cannot be cured, it can be

controlled.

- It is clear risk factor for periodontitis.

- In general, no difference in impact has been determinedbetween type I & Type II.


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Kinane found that,.direct relationship while, Taylor et al.bi-

directional relationship.

A study on Pima Indians showed an odds ratio of 2.8 to 3.4 for

developing periodontitis in Type II diabetics to non diabetics.


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Diabetes does not cause gingivitis or periodontitis but..

- It alters the response of the periodontal tissues to local factors,

- hastening bone loss and- delaying post surgical healing of periodontal tissues.

Frequent perio. abscess is important feature of perio. disease

in diabetics.

Glucose ^es in blood and gingival fluid > ^es in bact. Activity +

polymorphonuclear leukocyte > decrease in collagen synthesis.


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OBESITY: (BMI _> 30)

Involvement of hyper-inflammatory state and aberrant lipid

metabolism as well as the pathway of insulin resistance =enhanced breakdown of periodontal tissue support.

Number of recent studies point to a positive association.

Saito et al.waist to hip ratio, BMI, and body fat .significant

risk indicators.

There are only few cross-sectional studies, so, inferences on

temporality or mechanisms are not possible.

CANCER:


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CANCER:

Patients who have cancer and who undergo chemotherapy and

radiation therapy may experience significant deleterious oral

complications, including oral mucositis, xerostomia, radiation-

induced dental caries and even osteoradionecrosis.

Opportunistic infections such as Candida albicans have been

shown to increase in frequency with mucositis andimmunosuppression.

The antibiotics and steroids used to treat these infections can

result in secondary infections by the normal oral flora.


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DIETARY FACTORS:

i. CALCIUM:

- Nishida & co-workers evaluated the role

- The group who ingested lower levels of Ca in diet,. Increased

risk.

- Some authors showed that, women (20-30) had lower serum

calcium levels showed significantly higher risk (odds: 6.1)


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ii. VITAMIN C:

- Maintains health of gingiva.

- Severe vit. C deficiency: SCOBUTIC gingivitis.

- NHANES III (1988-1992): less intake of vit. C = increased risk ,specially among current tobacco users.

- Actual mechanism is not clear.


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MEDICATIONS:

i. PHENYTOIN:

ii. CYCLOSPORIN:iii. DIHYDROPYRIDINES:

- Overgrowth of gingiva.

- Gross increase in size: dramatic expansion of connective tissue

component.

- t/t: replacement of a drug & perio theray or surgery.

STRENGTH OF ASSOCIATION OF MODIFIABLE AND NON


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STRENGTH OF ASSOCIATION OF MODIFIABLE AND NON

MODIFIABLE FACTORS WITH DESTRUCTIVE PERIODONTAL

DISEASE.


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RISK INDICATORS FOR PERIODONTAL DISEASE

HIV/AIDS:

It has been hypothesized that, the immune dysfunction

associated increases susceptibility.

Studies revealed, HIV/AIDS patients had severe necrotizingulcerative periodontitis.

Also higher risk for periodontal pockets and CAL.


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OSTEOPOROSIS:

It is systematic factor..oral bone, (alveolar process with peri.

Infection).

From the assessment of osteoporosis in the jaws by dual

photon absorptiometry, it was found that reduction in total

skeletal mass is directly related to reduction in mandibulardensity. (Chesnut, Henrikson et al)


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INFREQUENT DENTAL VISITS:

Failure to visit the dentist regularly as a risk factor for

peridontitis is controversial.

One study demonstrated an increased risk for severe

periodontitis in patients who had not visited the dentist for 3 or

more years.

Whereas another demonstrated that there was no more loss of

attachment or bone loss in individuals who did not seek dental

care over a 6 year period.

RISK MARKERS/ PREDICTORS FOR PERIODONTAL


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RISK MARKERS/ PREDICTORS FOR PERIODONTAL

DISEASE

POOR ORAL HYGIENE:

Since bacterial plaque is by far the most important etiologicagent for the occurrence of periodontal diseases (for review,

see Kornman and Le, 1993), it is evident that the full mouth

assessment of the bacterial load must have a pivotal impact in

the determination of the risk for disease recurrence.

Studies to date have not identified the level of plaque infection

compatible with maintenance of periodontal health.


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However, in a clinical set-up, a percentage of tooth surfaces

covered by visible plaque of 20-40% might be tolerable in most

patients.

It is important to realize that the full mouth plaque score has to

be related to the host response of the patient, i.e. compared to

inflammatory parameters.


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PREVIOUS HISTORY OF PERIODONTAL DISEASES:

History of previous periodontal disease is a good clinical

predictor of risk for future disease.

Patients with the most severe existing loss of attachment are at

the greatest risk for future loss of attachment.


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PART: II


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SUBJECTIVE RISK ASSESSMENT

The patient's risk assessment for periodontitis may be

evaluated on the basis of a number of clinical conditionswhereby no single parameter displays a more paramount role.

The entire spectrum of risk factors and risk indicators ought to

be evaluated simultaneously.

For this purpose, a functional diagram has been constructed

including the following aspects:


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1. Percentage of bleeding on probing,

2. Prevalence of residual pockets greater than 4 mm (3-5 mm),

3. Loss of teeth from a total of 28 teeth,4. Loss of periodontal support in relation to the patient's age,

5. Systemic and genetic conditions, and

6. Environmental factors, such as cigarette smoking.


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Each parameter has its own scale for minor, moderate and

high-risk profiles.

Modifications may be made to the functional diagram if

additional factors become important according to new evidence.


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1. PERCENTAGE OF SITES WITH BLEEDING ON PROB ING

(BOP)

Bleeding on gentle probing represents an objective

inflammatory parameter which has been incorporated into index

systems for the evaluation of periodontal conditions (Le and

Silness, 1963; Mhlemann and Son, 1971).


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Although there is no established acceptable level of prevalence

of bleeding on probing in the dentition above which a higher risk

for disease recurrence has been established.

a BOP prevalence of 25% has been the cut-off point between

patients who maintained periodontal stability for 4 years and

patients with recurrent disease in the same time frame in a

prospective study in a private practice (Joss et al, 1994).


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Further evidence of BOP percentages between 20 and 30%

determining a higher risk for disease progression originates

from studies of Claffey et al (1990) and Badersten et al (1990).

In assessing the patient's risk for disease progression, BOP

percentages reflect a summary of the patient's ability to perform

proper plaque control, the patient's host response to thebacterial challenge and the patient's compliance, especially

when only few residual pockets remain after active periodontal

therapy.


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The percentage of BOP, therefore, is used as the first risk factor

in the functional diagram of risk assessment (Fig. 1).

The scale runs in a quadratic mode with 4, 9, 16, 25, 36 and >

49% being the critical values on the vector.

Individuals with low mean BOP percentages (< 10% of thesurfaces) may be regarded as patients with a low risk for

recurrent disease (Lang et al, 1990), while patients with mean

BOP percentages > 25% should be considered to be at high

risk for periodontal breakdown.


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2. PREVALENCE OF RESIDUAL POCKETS 5 MM (RESIDUAL

POCKET GREATER THAN 4 MM):

The enumeration of the residual pockets with probing depths

greater than 4 mm represents(to a certain extent) the degree of

success of periodontal treatment rendered.

Although this figureper se does not make much sense, whenconsidered as a sole parameter, the evaluation in conjunction

with other parameters such as bleeding on probing and/or

suppuration will reflect existing ecological niches from and in

which reinfection might occur.


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It is, therefore, conceivable that periodontal stability in a

dentition would be reflected in a minimal number of residual

pockets.

Presence of high frequencies of deep residual pockets and

deepening of pockets during supportive periodontal care has, in

fact, been associated with high risk for disease rogression

(Badersten et al, 1990; Claffey et al, 1990).


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In assessing the patient's risk for disease progression, the

number of residual pockets with a probing depth of5 mm is

assessed as the second risk indicator for recurrent disease in

the functional diagram of risk assessment (Fig. 1).

The scale runs in a linear mode with 2, 4, 6, 8, 10 and 12%

being the critical values on the vector.

Individuals with up to 4 residual pockets may be regarded as

patients with a relatively low risk, while patients with more than

8 residual pockets as individuals with high risk for recurrentdisease.


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3. Loss of teeth from a total of 28 teeth

Although the reason for tooth loss may not be known, the

number of remaining teeth in a dentition reflects thefunctionality of the dentition.

Mandibular stability and individual optimal function may be

assured even with a shortened dental arch of premolar topremolar occlusion, i.e. 20 teeth.


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The shortened dental arch does not seem to predispose the

individual to mandibular dysfunction (Witter et al, 1990, 1994).

However, if more than 8 teeth from a total of 28 teeth are lost,

oral function is usually impaired (Kyser, 1981, 1994, 1996).

Since tooth loss also represents a true end point outcomevariable reflecting the patient's history of oral diseases and

trauma, it is logical to incorporate this risk indicator as the third

parameter in the functional diagram of risk assessment (Fig. 1).

The number of teeth lost from the dentition without the third


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molars (28 teeth) is counted, irrespective of their replacement.

The scale runs also in a linear mode with 2, 4, 6, 8, 10 and 12being the critical values on the vector.

Individuals with up to 4 teeth lost may be regarded as patients in

a low risk category, while patients with more than 8 teeth lostmay be considered as being in a high-risk category.

Rationale for this stems from the significance of further tooth loss

in terms of preservation of the function of the dentition.

4 Los s o f per iodon tal sup po rt in re lat ion to the pat ient 's


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4. Los s o f per iodon tal suppo rt in relat ion to the pat ient s

age

The extent and prevalence of periodontal attachment loss (i.e.

previous disease experience and susceptibility), as evaluatedby the height of the alveolar bone on radiographs, may

represent the most obvious indicator of subject risk when

related to the patient's age.

In light of the present understanding of periodontal disease

progression, and the evidence that both onset and rate of

progression of periodontitis might vary among individuals and

during different time frames (Van der Velden, 1991), it has to berealized that previous attachment loss in relation to the patient's

age does not rule out the possibility of rapidly progressing

lesions.


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Therefore, the actual risk for further disease progression in a

given individual may occasionally be underestimated.

Hopefully, the rate of progression of disease has been

positively affected by the treatment rendered and, hence,

previous attachment loss in relation to patient's age may be a

more accurate indicator during SPT than before active

periodontal treatment.


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Given the hypothesis that a dentition may be functional for the

most likely life expectancy of the subject in the presence of a

reduced height of periodontal support (i.e. 25-50% of the root

length), the risk assessment in treated periodontal patients may

represent a reliable prognostic indicator for the stability of the

overall treatment goal of keeping a functional dentition for a

lifetime (Papapanou et al, 1988).

Th ti ti f th l f l l b i f d i th


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The estimation of the loss of alveolar bone is performed in the

posterior region on either peri-apical radiographs, in which the

worst site affected is grossly estimated in per cent of the root

length or on bitewing radiographs in which the worst siteaffected is estimated in millimeter.

On bitewing radiographs, one millimeter is considered to be

equal to 10% bone loss.

The percentage is then divided by the patient's age.

Thi lt i f t


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This results in a factor.

As an example, a 40-year-old patient with 20% of bone loss atthe worst affected posterior site would score BL/Age = 0.5.

Another 40-year-old patient with 50% bone loss at the worst

affected posterior site would score BL/Age = 1.25.


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In assessing the patient's risk for disease progression, the

extent of alveolar bone loss in relation to the patient's age isestimated as the fourth risk indicator for recurrent disease in the

functional diagram of risk assessment (Fig. 1).

The scale runs in increments of 0.25 of the factor BL/Age, with

0.5 being the critical value to discriminate between low and

moderate risk and 1.0 being the value for moderate and high

risk.


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This, in turn, means that a patient who has lost a higher

percentage of posterior alveolar bone than his/her own age is athigh risk regarding this vector in a multi-factorial assessment of

risk.

I b d h h i i f l h i


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It may be argued that the incorporation of only the worst site

with bone loss in the posterior segment may overestimate an

individual's rate of periodontal destruction when only an

isolated advanced bony lesion is present due to local etiologicfactors, while an underestimation of the rate of destruction may

exist in a case of generalized advanced disease.

Nevertheless, in patients successfully treated for periodontitis it

has recently been demonstrated that the worst site with bone

loss in the posterior segment may, indeed, represent the past

history of destruction of the entire dentition (Persson et al,

2003).


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5. SYSTEMIC AND GENETIC ASPECTS:

In assessing the patient's risk for disease progression, systemic

factors, if known, are only considered as the fifth risk indicatorfor recurrent disease in the functional diagram of risk

assessment (Fig. 1).

In this case, the area of high risk is marked for this vector.

If not known or absent, systemic factors are not taken into

account for the overall evaluation of risk.

R h th i ti d/ dif i i fl i


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Research on the association and/or modifying influence in

susceptibility and progression of periodontitis of physical or

psychological stress is sparse (Cohen-Cole et al, 1981; Green

et al, 1986; Freeman and Goss, 1993).

The hormonal changes associated with this condition, however,

are well documented (Selye, 1950).


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6. CIGARETTE SMOKING:

In assessing the patient's risk for disease progression,

environmental factors such as smoking must be considered asthe sixth risk factor for recurrent disease in the functional

diagram of risk assessment (Fig. 1).

While non-smokers (NS) and former smokers (FS; more than 5years since cessation) have a relatively low risk for recurrence

of periodontitis, the heavy smokers (HS; as defined by smoking

more than one pack per day) are definitely at high risk.


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Occasional smokers (OS; < 10 cigarettes a day) and moderate

smokers (MS; 10-19 cigarettes a day) may be considered at

moderate risk for disease progression.

CALCULATING THE PATIENT'S INDIVIDUAL PERIODONTAL RISK


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ASSESSMENT (PRA) Based on the six parameters specified above, a multi-functional

diagram is constructed for the PRA.

In this diagram, the vectors have been formed on the basis of

the scientific evidence available.

It is obvious that ongoing validation may result in slight

modifications.


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A low PRA patient has all parameters within the low-risk

categories or - at the most - one parameter in the moderate-risk

category (Fig. 2).


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A high PRA patient has at least two parameters in high risk


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category.

In a high-risk patient who yields high BOP percentages and


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high numbers of residual pockets (Fig. 5), the patient's risk for

disease progression may be reduced into the moderate

category if further periodontal therapy is provided.

These two parameters (BOP and residual pockets) are easily

affected by therapy, while other parameters, such as numbers

of missing teeth or systemic and genetic factors are eitherirreversible and cannot be reduced or may only be affected with

great additional efforts (smoking cessation).

The factor determining the percentage of experienced alveolar


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bone loss in relation to the patient's age may be reduced only

during a time period of several years.


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BIOMARKERS FOR ASSESSMENT OF PERIODONTAL

DISEASE


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DISEASE (NEED) Traditional clinical measurements used for periodontal

diagnosis are indicators of previous periodontal disease

rather than present disease activity.

So need for development of new diagnostic tests that can

detect the presence of active disease, predict futuredisease progression and evaluate the response to

periodontal therapy.


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Advances in oral and periodontal disease diagnostic

research are moving toward methods whereby periodontal

risk can be identified and quantified by objective measuressuch as biomarkers.

Biomarkers may be defined as a substance that is


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measured objectively and evaluated as an indicator of

normal biologic processes, pathogenic processes , and

pharmacologic responses to a therapeutic intervention.

Biomarkers, whether produced by normal healthy

individuals or by individuals affected by specific systemic

diseases, are tell-tale molecules that could be used tomonitor health status, disease onset, treatment response

and outcome.

Informative biomarkers can further serve as early sentinelsof disease.

BIOMARKERS IN GINGIVAL CREVICULAR FLUID (GCF)

AND SALIVA


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AND SALIVA

According to Armitage (2004), more than 65 GCF constituents

have been evaluated as potential diagnostic markers ofperiodontal disease progression.

These markers can be divided into three groups: host-derived

enzymes and their inhibitors, inflammatory mediators and host-response modifiers, and byproducts of tissue breakdown.

BIOMARKERS IN GINGIVAL CREVICULAR FLUID (GCF) AND SALIVA


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CURRENT METHODS FOR PERIODONTAL RISK


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ASSESSMENT : In Periodontology, current methods to assess periodontal risk

factors include:

- Periodontal Risk Calculator (PRC),

- hexagonal risk diagram for Periodontal Risk Assessment

(PRA),

- PreViser Risk CalculatorTM, the periodontal risk assessment

model developed by Chandra, and

- simplified method (UniFe) (Union of European Railway

Industries) for periodontal risk assessment.

The Periodontal Risk Calculator (PRC) and the Periodontal

A t T l (PAT)


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Assessment Tool (PAT):

Page et al. developed a computer-based risk assessment tool,

the PRC, for objective, quantitative assessment of risk.

The calculation of risk using this model is based on

mathematically derived algorithms that assign relative weights

to nine factors including patient age, smoking history, diagnosisof diabetes, history of periodontal surgery, pocket depth,

furcation involvements, restorations or calculus below the

gingival margin, radiographic bone height and vertical bone

lesions.

The PRC assigns the individual a level of risk on a scale from 1

(l t i k) t 5 (hi h t i k)


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(lowest risk) to 5 (highest risk).

The Periodontal Assessment Tool (PAT) is an integral part ofthe Oral Health Information Suite (OHIS)TM (PreViser, Inc.,

Mount Vernon, WA; www.previser.com) and is considered as a

modification of the PRC method.

Following the input of only twenty-three items taken from a

ti i d t l i ti th t t li i ti


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routine periodontal examination, the system generates linguistic

and numeric periodontal diagnoses and a risk score for future

disease, and prepares a report in two versions; one for thedentists clinical documentation and another for the patient.

The traditional documentation of six pocket depth

measurements per tooth has been reduced to the deepestpocket for each sextant. PAT also requires the greatest distance

of the bone crest to the cemento-enamel junction determined

from radiographs, again using one measurement for each

sextant and three categories: 4 mm.

The hexagonal risk diagram for Periodontal Risk Assessment

(PRA)


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(PRA)

Lang and Tonetti28 described a functional diagram based on six

parameters for use in estimating an individuals risk for progression of

periodontitis.

The authors provided evidence supporting the inclusion of each

parameter within the diagram.

The combined assessment of each parameter allows the assessment

of the risk level for disease progression on an individual basis.

Minor modifications of the PRA model described by Lang and Tonetti

have been published later.

The periodontal risk assessment model developed by Chandra


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In 2007, Chandra31 evaluated a novel periodontal risk assessment

model in patients presenting for dental care.

This new model based on the periodontal risk assessment model by

Lang and Tonetti where the following parameters are recorded:

- percentage of sites with bleeding on probing,

- number of sites with pocket depths 5mm,- number of teeth lost, bone loss/age ratio,

- Attachment loss/age ratio,

- diabetic and smoking status, dental status, other systemic factors and

risk determinants.

The simplified method (UniFe) for periodontal risk


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assessment

In 2009, Trombelli and co-workers proposed a new objective

method (UniFe) (Union of European Railway Industries) in order tosimplify the risk assessment procedures.

Risk assessment according to UniFe method is based on five

parameters, derived from the patient medical history and clinicalrecordings.

parameters are as follows: smoking status, diabetic status (both

type 1 and type 2), number of sites with probing depth 5mm,bleeding on probing score, and bone loss/age records.

THE CURRENT METHODS FOR PERIODONTAL RISKASSESSMENT; ARE WE ON THE RIGHT TRACK?


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Regarding the literature, confusing trials for setting risk

elements for periodontal disease could be found.

For instance, as reviewed by Borrel and Papapanou, a

distinction was made between putative factors (non-modifiable

background factors) and modifiable factors (environmental,acquired, and behavioral).


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Accordingly, age, gender, and gene polymorphisms were

considered as non-modifiable background factors, whereasmicrobiota, smoking, diabetes mellitus, osteoporosis, HIV

infection, and psychosocial factors were considered as

modifiable background factors.

On the other side, some authors tended to consider smoking,


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, g,

diabetes, pathogenic bacteria, and microbial tooth deposits as risk

factors for periodontitis, whereas age, gender, socioeconomic status,

stress, and genetic factors were considered as risk determinants, andHIV infection, osteoporosis, and infrequent dental visits were

considered as risk indicators for periodontitis.

However, it seems to be that there is a recent agreement to acceptspecific bacteria, cigarette smoking, and diabetes mellitus as the

major established risk factors for periodontitis.

The rest ofrisk elements for periodontitis still need to be confirmed

in future.

Regarding the current methods for periodontal risk assessment,


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it seems to be that the use of risk calculators holds much

promise in the clinical practice. However, the lack of such

evidence still exists.

Chandra and Trombelli et al. tried to modify the hexagonal risk

diagram for periodontal risk assessment of Lang and Tonetti,

and found acceptable results at detecting potential risk groups.

Although the validation and accuracy of the PreViser Risk


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g y

CalculatorTM and the information required for its use have been

reported, the whole software seems to more powerful in

demonstrating a detailed description of the patients current situation(i.e. Diagnosis), and to give several treatment options related to every

individual case.

In other words, this method is more likely to present a comprehensiveand systematic approach to clinical decision-making for periodontists.

Therefore, it is a little bit far away from being a tool that concentrates

on important and the most strong risk elements for periodontitis.

However, as is the case with the Lang/Tonetti tool, the


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functional diagram of Chandra and of Trombelli et al. should be

only used during SPT to evaluate possible progression of the

periodontal disease and not for patients who visit the dentalclinic for the first time.

That would be more plausible.

SUMMARY

The role of risk factors and risk assessment in the prediction of


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The role of risk factors and risk assessment in the prediction of

clinical periodontal outcomes has been a subject of much

interest.

To date, it is accepted that specific pathogenic bacteria

(Porphyromonas gingivalis, Tannerella forsythia, and

Aggregatibacter actinomycetemcomitans), cigarette smoking,

and diabetes mellitus are the major established risk factors for

periodontitis.

Although several approaches have been developed to assess


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Although several approaches have been developed to assess

the factors which may interfere with periodontal diseases onset

and/or progression, some contradictions regarding the

classification, the definition, and the assumed implemented

factors do exist among all these methods.

REFERENCES

Chester W. Douglass. Risk assessment and management of


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g g

periodontal disease. JADA, Vol. 137 http://jada.ada.org

November 2006.

Aous Dannan. Periodontal Risk Assessment; Are We On The

Right Track.AOSR2011;1(3):162-167.

Lei Zhang, Bradley S. Henson, Paulo M. Camargo & David T.

Wong. The Clinical Value Of Salivary Biomarkers For

Periodontal Disease. Periodontology 2000, Vol. 51, 2009, 2537.

Gun-Bak Rheu, Suk Ji, Jae-Jun Ryu. Risk assessment for

clinical attachment loss of periodontal tissue in Korean adults. J

Adv Prosthodont 2011;3:25-32.

REFERENCES


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Raul I. Garcia, Martha E. Nunn & Thomas Dietrich. Risk

calculation and periodontal outcomes. Periodontology 2000,

Vol. 50, 2009, 6577.

A. Kazemnejad, F. Zayeri, A.R. Rokn, and M.J. Kharazifard.

Prevalence and risk indicators of periodontal disease among

highschool students in Tehran. Eastern Mediterranean Health

Journal, Vol. 14, No. 1, 2008 119.


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THANK YOU

ASSESSMENT OF periodontal risk factors and indicators.pptx

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