Prognostic factors affecting the short-term efficacy of non-surgical treatment of chronic periodontitis: a multilevel modelling analysis

doi:10.21203/rs.3.rs-27363/v1

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Prognostic factors affecting the short-term efficacy of non-surgical treatment of chronic periodontitis: a multilevel modelling analysis

https://doi.org/10.21203/rs.3.rs-27363/v1

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published 01 Jun, 2021

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Objective This current study is aimed to analyze the prognostic factors affecting the short-term efficacy of non-surgical treatment of patients in periodontitis from stage II to stage IV by the multilevel modelling analysis.

Materials and Methods A total of 58 patients of chronic periodontitis were included in this study. Patients were clinically explored before and 3 months after the treatment, with the data of Δ probing depth (PD) [Δ PD = baseline PD – finial probing depth (FPD)] as the outcome variables. All the data were divided into site level, tooth level and patient level to construct a multi-layer linear model.

Results Compared with the mesial sites and distal sites of the multi-rooted teeth, the number of PD ≥ 5mm or PD < 5mm after the treatment was significantly different ( P < 0.05), and the proportion of PD < 5mm was higher in mesial sites. The null model showed that Δ PD varied greatly between groups at various levels ( P <0.001), with prediction variable of site level, tooth level, and patient level accounted for 66%, 18%, and 16% of the overall difference, respectively. The complete model showed that the Δ PD of smokers was significantly lower than that of non-smokers ( P < 0.001). The Δ PD of the mesial and distal sites was larger than that of the buccolingual central site ( P < 0.001). The Δ PD of single-rooted teeth was larger than that of multi-rooted teeth ( P < 0.001). The baseline PD, tooth mobility (TM), bleeding index (BI), clinical attachment loss (CAL) were significantly negatively correlated with Δ PD ( P < 0.001).

Conclusions Patients with periodontitis from stage II to stage IV, who are non-smoking, have good compliance, good awareness of oral health, and low percentage sites with PD ≥ 5mm at baseline, single rooted teeth with hypomobility, less CAL and lower BI and sites of mesial or distal can obtain an ideal short-term efficacy of non-surgical treatment.

Dentistry

periodontitis

non-surgical treatment

multi-level linear model

prognosis

As a chronic disease, the risk factors that have been identified for the periodontitis include genetics, systemic diseases, lifestyle, sociological and environmental factors [1, 2]. Meanwhile, the new classification system for periodontitis jointly determined by the American Academy of Periodontology (AAP) and the European Federation of Periodontology (EFP) also reflects the current focus of scholars on judging the progress of individual periodontitis by combining risk factors [3]. The combination of various risk factors not only makes the state of periodontitis and the progression vary in different individuals, but also represent great differences in treatment response.

Periodontal non-surgical treatment is a process of thoroughly removing the biofilm and calculus on the tooth root surface to reduce the total amount of bacteria below the individual disease threshold level ,which has been proved its overall efficacy by previous studies[4, 5]. Meanwhile, it is necessary to integrate various factors to speculate whether the patients will respond well to the non-surgical treatment.

A traditional multivariate regression model was often used to process periodontal data, which ignores the three different levels involved in periodontal data: patients, teeth and sites. It will underestimate the standard errors and give potentially misleading results when the data at the lower level is averaged to the higher level. Therefore, Hierarchical linear model (HLM) can be used to process multi-level nested data. It can not only decompose the variation at different levels,but also analyze the interaction between different levels to accurately separate the effect of prediction variables at all levels. The HLM has been widely used in the periodontal studies since first proposed by Sterne et al. [6] in1988. In addition, Albandar et al. [7] have applied HLM to study the predictors of periodontal disease progress at the level of patient individuals and teeth position. Vettore et al. [8] used this method to analyze the relationship between the prevalence of periodontal disease, geographical location and social status. Furthermore, the HLM has also been applied in processing the nested data of Prosthodontics and Orthodontics [9, 10]. This study was designed to analyze the prognostic factors affecting the short-term efficacy of non-surgical treatment of chronic periodontitis patients by the method of HLM.

Patients

The study was approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University and the informed consent forms were signed by the involved individuals. Patients from the Stomatology of The First Affiliated Hospital of Dalian Medical University from June 2018 to June 2019 were included in this study. A questionnaire was distributed among all the patients to obtain personal information. The inclusion criteria included: 1) patients with clinically stage Ⅱ to stage Ⅳ periodontitis; 2) aged between18 and 80; 3) at least 16 teeth remained in the mouth (excluding the third molar). The exclusion criteria included: 1) refuse non-surgical periodontal therapy; 2) have basic periodontal treatment history; 3) antibiotics usage within one month; 4) pregnancy and lactation; 5) systemic disease history; 6) periodontal surgery history;7) serious mental illness and cognitive impairment.

Clinical data collection

The demographic data of the patients included in the study were recorded, and the patients were treated with non-surgical periodontal treatment. A full-mouth set of radiographs were obtained and clinical examinations were performed before treatment. The whole teeth were divided into four quadrants (upper left, lower left, upper right and lower right). Six sites (mesio-buccal, disto-buccal, mid-buccal, mesio-lingual, disto-buccal, mid-lingual) per tooth were measured and recorded, excluding the third molars. Probing depth (PD), clinical attachment loss (CAL), bleeding index (BI), tooth mobility (TM) were probed with periodontal probe. After the treatment, oral hygiene instruction regarding brushing and inter-dental cleaning, and regular follow-up visits at 2 weeks, 1 month and 3 months were informed. Finial probing depth (FPD) was measured at the 3 months after the non-surgical periodontal treatment. Excluded patients who were not observed in the 3 months. According to the inclusion flow chart in Fig. 1, 58 patients were ultimately included in this study. All the above procedures were carried out by two experienced periodontists, who were trained to adequate levels of accuracy and reproducibility for the various clinical parameters and indices to be used. The repeatability test showed that the kappa value of each index was > 0.75, which proved that the consistency was good.

The collected data were divided into three levels, including site level, tooth level and patient level.

Therein, the site level included: 1) baseline PD; 2) site location (mesio-buccal, disto-buccal, mid-buccal, mesio-lingual, disto-lingual, mid-lingual).

The tooth level included: 1) the BI of the tooth was detected for 30 seconds (the BI of tooth with higher buccal and lingual surface was recorded as the BI of tooth) (0–5); 2) the TM of the tooth (0 ~ III°); 3) CAL: measured by the distance from the cementoenamel junction to the bottom of the periodontal pocket (the maximum CAL of buccal and lingual surface of each tooth was recorded, and the mean CAL of buccal and lingual was calculated); 4) tooth type: single-rooted and multi-rooted.

The patient level included: 1) age; 2) gender; 3) smoking status; 4) body mass index (BMI); 5) compliance: according to the follow-up situation, the patients were divided into the complete compliance group (patients who participate in each follow-up on time, and perform well in brushing and inter-dental cleaning) and irregular compliance group (absent during the follow-up or / and occasionally use floss or interdental brush); 6) education: high school degree or below, bachelor's degree and postgraduate degree or above; 7) oral health awareness (OHA) score: four questions about OHA of patients, the answers were counted as very important, generally important and unimportant, each of which was scored as 3, 2 and 1 respectively. Each patient obtained a minimum score of 4, and a maximum score of 12, which was recorded as the OHA score [11]; 8) the percentage sites with PD ≥ 5 mm at baseline.

Statistical analysis

The sites with baseline PD < 5 mm can obtain considerable outcomes after the periodontal non-surgical treatment. Hence, the patients of this study were all sites with a baseline PD ≥ 5 mm, and define the HLM outcome variable (ΔPD = baseline PD – FPD). The HLM is composed of fixed effect and random effect. Therein, the value of fixed effect refers to the regression coefficient (the average slope and intercept), and the value of random effect refers to the variance of the residual (the specific part of different groups). Moreover, HLM analysis starts with a null model. The null model means that no variables are added to the model. This mode is used to estimate whether the overall variability of dependent variables is significant and attribute it to the patient, tooth, and site levels. Then, according to the purpose of the study, the random effects model and the complete mixed-effects model are constructed by adding the prediction variables of each level.

All data was manifested as count (percentage) or mean ± standard deviation (SD) and were imported into SPSS 22.0 software (IBM Corp., Armonk, NY, USA), and HLM 6.0 software (Scientific Software International Inc., Lincolnwood, USA) for analysis. The comparison of continuous measurement data was analyzed by Student t test of paired independent samples, the comparison of counting data was analyzed by Pearson x² test, and the nested structure data was analyzed by a multi-layer linear model method. A P value < 0.05 was regarded as statistically significant.

Demographic data and variables assignment

Table 1 revealed the demographic data and variables assignment of this study. A total of 58 patients, 1162 teeth and 3126 sites were included in this study.

Table 1

The demographic data and variables assignment of this study
Variables	Assignment	Mean ± standard deviation (SD)
Patient level (Third level)		N = 58
Age, years	Continuity variable	45.00 ± 12.56
Gender	Male = 1/Female = 2	34/24
Smoking	Smoking = 0/Non-smoking = 1	40/18
BMI, kg/m²	Continuity variable	24.97 ± 2.57
Compliance	Complete compliance = 1/Irregular compliance = 2	32/26
Percentage of baseline PD ≥ 5 mm	Continuity variable	34.75 ± 16.24
OHA score, point	Continuity variable	6.52 ± 1.23
Education	High school degree or below = 1/Bachelor's degree = 2/Postgraduate degree or above = 3	27/24/7
Tooth level (Second level)		N = 1162
Baseline BI	0/1/2/3/4/5	0/102/342/450/268/0
Tooth type	Single tooth = 1/ multiple teeth = 2	708/454
TM, degree	0 degree = 0/Ⅰ degree = 1/Ⅱ degree = 2/III degree = 3	936/138/71/17
CAL, mm	Continuity variable	4.26 ± 1.22
Site level (First level)		N = 3126
Baseline PD	Continuity variable	5.69 ± 1.08
Site location	mesio-buccal, disto-buccal, mesio-lingual, disto-lingual sites = 1/mid-buccal, mid-lingual site = 2	2714/412
Note: BMI, body mass index; PD, probing depth; OHA, oral health awareness; BI, bleeding index; TM, tooth mobility; CAL, clinical attachment loss.

Description and comparison of PD at different sites before and after treatment

At baseline, there were 1739 sites with PD ≥ 5 mm in single-rooted teeth and 1387 sites with PD ≥ 5 mm in multi-rooted teeth. After 3 months of non-surgical periodontal treatment, 1341 sites PD < 5 mm and 398 sites PD ≥ 5 mm were found in single-rooted. There were 865 sites with PD < 5 mm and 522 sites with PD ≥ 5 mm in multi-rooted. With PD ≥ 5 mm or PD < 5 mm as the boundary, the number of 6 sites of single-rooted teeth and multi-rooted teeth were compared in pairs. The results showed that in multi-rooted teeth(Table 2), there was a significant difference in the number of sites with PD ≥ 5 mm or PD < 5 mm after treatment between mesio-buccal and disto-buccal (P < 0.05), and there was a higher proportion of PD < 5 mm in the mesio-buccal. Moreover, there was a significant difference in the number of sites with PD ≥ 5 mm or PD < 5 mm after treatment between the mesio-lingual and disto-lingual (P < 0.05). The proportion of PD < 5 mm in the mesio-lingua was higher, and there was no statistical difference in the rest. In single-rooted teeth (Table 3), there was no statistical difference in the number of sites with PD ≥ 5 mm or PD < 5 mm at 6 sites after the treatment.

Table 2

Comparison of PD ≥ 5 mm or < 5 mm at each site after 3 months of multi-rooted teeth treatment
	PD༜5 mm		PD ≥ 5 mm		Total	χ²	P value
	Number of sites	Constituent ratio	Number of sites	Constituent ratio	Total	χ²	P value
Mesio-buccal site	203	75.5%	66	24.5%	269	1.11	0.29
Mesio-lingual site	206	71.5%	82	28.5%	288	1.11	0.29
Mesio-buccal site	203	75.5%	66	24.5%	269	23.37	0.00^*
Disto-buccal site	166	56.1%	130	43.9%	296	23.37	0.00^*
Disto-buccal site	166	56.1%	130	43.9%	296	0.11	0.74
Disto-lingual site	182	57.4%	135	42.6%	317	0.11	0.74
Mesio-lingual site	206	71.5%	82	28.5%	288	13.07	0.00^*
Disto-lingual site	182	57.4%	135	42.6%	317	13.07	0.00^*
Mid-buccal site	49	47.6%	54	52.4%	103	0.38	0.54
Mid-lingual site	59	51.8%	55	48.2%	114	0.38	0.54
Note: PD, probing depth. ^* P value < 0.05.

Table 3

Comparison of PD ≥ 5 mm or < 5 mm at each site after 3 months of single-rooted teeth treatment
	PD༜5 mm		PD ≥ 5 mm		Total	χ²	P value
	Number of sites	Constituent ratio	Number of sites	Constituent ratio	Total	χ²	P value
Mesio-buccal site	303	77.3%	89	22.7%	392	0.15	0.72
Mesio-lingual site	277	78.5%	76	21.5%	353	0.15	0.72
Mesio-buccal site	303	77.3%	89	22.7%	392	0.16	0.69
Disto-buccal site	324	78.5%	89	21.5%	413	0.16	0.69
Disto-buccal site	324	78.5%	89	21.5%	413	0.22	0.64
Disto-lingual site	299	64.8%	89	35.2%	388	0.22	0.64
Mesio-lingual site	277	78.5%	76	21.5%	353	0.21	0.65
Disto-lingual site	299	64.8%	89	35.2%	388	0.21	0.65
Mid-buccal site	49	77.8%	14	22.2%	63	1.81	0.18
Mid-lingual site	89	68.5%	41	31.5%	130	1.81	0.18
Note: PD, probing depth.

Multi-level modeling analysis

(1)

The null model

The results of the null model without any predictive variables (Table 4) showed that significant variations existed in all three levels (P < 0.001), which was necessary to build a multi-level linear model to explain the difference. In the null model variability at each individual level was obtained as percentage of the total variability calculated adding all estimates together. Therein, The majority of the variance in Δ PD was attributed to the site level (66%), followed by the tooth (18%) and patient levels (16%).

Table 4

The estimation results of null model
		Variance component	Chi square value	P value
Random effect part
Site level (First level)	0.79	0.62(66%)
Tooth level (Second level)	0.41	0.17(18%)	1904	0.000^***
Patient level (Third level)	0.38	0.15(16%)	453	0.000^***
Note: ^*** P value < 0.001

(2)

The random effects model

The results of the random effects model (Table 5), showed that the test for the intercept item test at level 3 was significant (P < 0.001), indicating that it was necessary to continue to include the variables of level 3 in the intercept item to explain differences. The random part of the baseline PD µ₂ slope was not significant (P > 0.05), then discarded the random slope and set it as a fixed effect. Meanwhile, independent variable slopes in TM, BI, CAL, and the baseline PD e₂₀ were significantly different (P < 0.001), and needed to be randomized in the next model.

Table 5

The random effects model
	Variance component	Chi square value	P value
Random effect part
Intercept µ₀₀	0.09	310.76	0.000^***
Baseline PD µ₂	0.01	317.49	༞0.5
Intercept e₀₀₀	0.89	82.36	0.000^***
TM	0.05	103.51	0.000^***
BI	0.01	52.22	0.024^*
CAL	0.01	65.62	0.001^**
Baseline PD e₂₀	0.03	123.24	0.000^***
Note: ^* P༜0.001,^ P༜0.01༌^* P༜0.05.

(3)

The mixed-effects model

All the clinical covariates of three levels were added to the model to build a mixed-effects model (Table 6). At the site level the model confirmed that mesial and distal sites were the areas where PD changes were greater than those observed at the buccolingual central site (P < 0.001). Meanwhile, the deeper the baseline PD, the greater the observed decrease in PD after non-surgical periodontal treatment (P < 0.001). At the tooth level, compared with multi-rooted teeth, the Δ PD of single-rooted teeth after periodontal non-surgical treatment was higher (P < 0.001). Meanwhile, there was a significant negative correlation between BI, TM, CAL and Δ PD at the baseline (P < 0.001). At the patient level, compared with the non-smokers, smoking had a significant negative impact on the chance of PD (P < 0.001). Δ PD were highly significant affected by patient compliance (P < 0.01), and the Δ PD of patients with complete compliance was higher than that with irregular compliance. The greater the percentage sites with PD ≥ 5 mm at baseline, that is, the patients with the poor initial full periodontal conditions, the ΔPD was relatively small (P < 0.01). In addition, the OHA score was positively correlated with the oral health awareness of patients and Δ PD (P < 0.01). However, there was no significant correlation between the age, gender, education level and BMI (P > 0.05).

Table 6

The mixed-effects model
	Coefficient	Standard deviation	Variance component	Inspection value	P value
Fixed effect part
Intercept	2.45	0.41		6.02^a	0.000^***
Site location	-0.3	0.05		-6.03^a	0.000^***
Baseline PD	0.30	0.03		9.60^a	0.000^***
Tooth type	-0.39	0.04		-8.82^a	0.000^***
TM	-0.32	0.04		-7.34^a	0.000^***
BI	-0.20	0.03		-7.17^a	0.000^***
CAL	-0.14	0.02		-5.93^a	0.000^***
Age	0.001	0.004		0.34^a	0.739
Gender	-0.09	0.07		-1.30^a	0.199
Smoking	-0.35	0.08		-4.36^a	0.000^***
Compliance	-0.21	0.07		-3.14^a	0.003^**
BMI	-0.01	0.01		-0.91^a	0.365
Percentage of baseline PD ≥ 5 mm	0.005	0.002		2.50^a	0.016^**
OHA score	0.07	0.03		2.35^a	0.023^**
Education	0.03	0.06		0.45^a	0.658
Random effect part
Intercept µ₀₀		0.14	0.02	611.03^b	0.047^*
Intercept e₀₀₀		0.96	0.93	94.36^b	0.000^***
BI		0.13	0.02	51.28^b	0.029^**
TM		0.22	0.05	104.47^b	0.000^***
CAL		0.10	0.01	64.87^b	0.001^**
Baseline PD e₂₀		0.18	0.03	129.10^b	0.000^***
-2logL	7176.81			912.75^c	0.000^***
Note: BMI, body mass index; PD, probing depth; OHA, oral health awareness; BI, bleeding index; TM, tooth mobility; CAL, clinical attachment loss.
^* P༜0.001,^ P༜0.01༌^* P༜0.05.
a, t value; B, x² value; C, x² value compared with the goodness of fit of the null model.

From the random effects of the complete model, there was a significant random effects in BI, TM, CAL and baseline PD,indicating that these factors are still affected by other clinical covariates, which can be further studied. Meanwhile, when all the clinical covariates and random errors at all levels are added into the mixed-effects model, the goodness of fit of the mixed-effects model is improved significantly compared with the null model (P < 0.001).

Currently, it is generally acknowledged that the PD ≥ 5 mm after 3 months of periodontal non-surgical treatment indicates that the treatment needs to be continued. Regarding this, Tomasi et al. [12] have put forward the concept of “periodontal pockets closure”, that is, after 3 months of periodontal treatment, the PD < 5 mm is regarded as a good indicator of non-surgical treatment effect. However, for many patients with moderate to severe periodontitis, the deep periodontal pockets perform obvious effect even though FPD > 5 mm after treatment, shows that the concept of “periodontal pockets closure” is not fully consistent with the efficacy of non-surgical periodontal treatment. Hence, in this study, the Δ PD was used to act as the result variable of the model.

The results of null model showed that the ΔPD was significant difference between the site level, tooth level and patient level, and these three levels accounted for 66%, 18%, and 16% of the overall variations, which indicated that the site level had the greatest impact on short-term efficacy of periodontal non-surgical treatment. The results of mixed-effects model showed that the mesial and distal sites showed significantly greater changes in PD after non-surgical periodontal therapy than buccolingual central site at the site level, which was similar to previous studies by D’Aiuto et al. [13]. In addition, other studies have also found that after non-surgical periodontal treatment of medium-depth periodontal pockets, the ΔPD was 1.2 mm, and those of deep periodontal pockets (PD ≥ 6 mm), the PD decreased by an average of 2.4 mm [14]. Similarly, this study also showed a positive correlation between Δ PD and baseline depth, which may be related to the control of inflammation after the treatment, the swollen gums subsided obviously, and the long epithelium formed on the root surface, which made the decrease of PD in deep periodontal pockets more obvious than in shallow periodontal pockets.

At the tooth level, the Δ PD of multi-rooted teeth was smaller than that of single-rooted teeth, which can be explained from three aspects. Firstly, single-rooted teeth were mainly located in the front of the dentition, with high treatment efficiency, and the gingival tissue in the anterior teeth area was thinner than that in the premolars or molars, with better healing degree. Secondly, the anatomical structure of multi-rooted teeth was complex, with complex root canal system, the presence of furcations, enamel pearl and root depression. Shi et al. [15] found that the furcation involvement seriously affected the reduction of PD in the molar, and the molar was considered to be the tooth with the poor prognosis [16]. Thirdly, the multi-rooted teeth often bear greater masticatory force than the single-rooted teeth. This model also demonstrated that teeth with severe CAL and hypermobility were associated with inferior prognosis, which indicated that the effect of non-surgical treatment on hopeless teeth or questionable teeth is limited and surgical treatment or extraction should be involved to achieve better outcome.

Smoking has been proved to be one of the main risk factors for the occurrence and development of periodontal diseases. Compared with non-smokers, smokers have deeper periodontal pockets and higher CAL, more obvious alveolar bone resorption, more severe gingival recession, and higher risk of teeth loss [17]. In this study, cigarette smoking negatively affects the outcome of non-surgical periodontal therapy: smokers had 0.35 mm less PD reduction than non-smokers, which was similar to the previous study by Bunaes et al. [18]. This may be related to the fact that the depth of periodontal pockets and the level of CAL of smokers were larger than that of non-smokers, and the treatment difficulty was correspondingly increased. In addition, because of the lower degree of tissue inflammation in smokers, during the process of periodontal exploration, the probe penetration was reduced, and the measured CAL was smaller than actual value. Moreover, the ecological environment in deep periodontal pockets of smokers was more difficult to change by simple mechanical debridement. Regarding this, the previous studies have found that after 3 months of periodontal treatment, a significant reduction in red and orange complexes was only observed in non-smokers. After 6 months of treatment, subcolonial bacterial recolonization of pathogenic bacteria was observed only in smokers, indicating that smokers were more likely to reconstruct pathogenic subgingival plaque biofilms than non-smokers [19].

Furthermore, compliance is another important factor that affected periodontal non-surgical treatment. In this study, after 3 months of treatment, patients in the complete compliance group had significantly higher Δ PD than those in the irregular compliance group. The result demonstrated that good compliance is essential to a successful periodontal treatment. Periodontitis, characterized by its painless property, the awareness of plaque control in patients will decreasing after treatment, so they no longer followed up, until the dysfunction such as more severe bleeding gums and hypermobility in teeth occurred. Lee et al. [20] found that patients with complete compliance had significantly lower rates of tooth loss during supportive periodontal therapy (SPT) than the patients with irregular compliance. Moreover, Robinson et al. [21] and Furuta et al. [22] have found that women had stronger anti-infection ability, and the oral health habits of women were better than men, and the overall prognosis of periodontal treatment of women was better than that of men [23]. However, in this study, the factors of age and gender showed no significant correlation, which may be related to the limited sample size. Meanwhile, the goodness of fit (− 2logL) of the final model was significantly different from that of the null model, which indicated that the difference was significantly improved after all the clinical covariates were added to the model, but there were still unexplained parts. Hence, the remaining research variables can be added to future studies to further explain the model, such as the factors of furcation involvement, pulp status, crown root ratio, direction of bone resorption, crowded degree of dentition, width of attached gingiva, subgingival plaque microorganisms, systemic diseases, and genetics.

The enlightenment of this study for clinicians is that the prognosis of periodontal non-surgical treatment for periodontitis patients with smoking, poor compliance and poor awareness of oral health may be poor. For this group, clinicians should emphasize the necessities of quitting smoking and SPT, strengthen oral hygiene instruction. Moreover, the multi-rooted teeth, teeth with severe TM, BI and CAL often suggest lower PD reduction, especially the buccolingual central site, which requires clinicians to fully consider the above factors when making the treatment plans for initial diagnosis. It is also necessary to focus on these teeth and sites during the long-term follow-up to prevent the further disease progression.

Patients with periodontitis from stage Ⅱ to stage Ⅳ, who are non-smoking, have good compliance, good awareness of oral health, and low percentage sites with PD ≥ 5 mm at baseline, single rooted teeth with hypomobility, less CAL and lower BI and sites of mesial or distal can obtain an ideal short-term efficacy of non-surgical treatment.

PD, Probing depth;

FPD, Finial probing depth

TM, Tooth mobility;

BI, Bleeding index;

CAL, Clinical attachment loss;

AAP, American Academy of Periodontology;

EFP, European Federation of Periodontology;

HLM, Hierarchical linear model;

BMI, Body mass index;

OHA, Oral health awareness;

SPT, Supportive periodontal therapy;

Acknowledgements

We would like to thank all the participants in the studies.

Authors’ contributions

HL, BW, AW, DZ, CM and QL participated in the clinical data collection, data analysis and data interpretation. HL, BW, AW, DZ and QL contributed to management of the clinical cases and interpretation of clinical data. HL and QL wrote and edited the manuscript. HL, BW and QL contributed to the critical revision of the manuscript. All authors read and approved the final manuscript.

Funding

This study was supported by a grant from the Liaoning Natural Science Foundation Project (No:2014023035).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

The Ethics Committee of the First Affiliated Hospital of Dalian Medical University approved this study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Contributor Information

Hui-Jie Liu, E-mail: [email protected]

Bo Wang, E-mail: [email protected]

Ao-Chen Wang, E-mail: [email protected]

Dan-Hong Zhang, E-mail: [email protected]

Cui Mao, E-mail: [email protected]

Qiu-Hong Li, E-mail: [email protected]

Tanner AC: Anaerobic culture to detect periodontal and caries pathogens. Journal of oral biosciences 2015, 57(1):18-26.
Chandki R, Banthia P, Banthia R: Biofilms: A microbial home. Journal of Indian Society of Periodontology 2011, 15(2):111-114.
Tonetti MS, Greenwell H, Kornman KS: Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. Journal of clinical periodontology 2018, 45 Suppl 20:S149-s161.
Badersten A, Nilveus R, Egelberg J: Effect of nonsurgical periodontal therapy. I. Moderately advanced periodontitis. Journal of clinical periodontology 1981, 8(1):57-72.
Drisko CL: Periodontal debridement: still the treatment of choice. The journal of evidence-based dental practice 2014, 14 Suppl:33-41.e31.
Sterne JA, Johnson NW, Wilton JM, Joyston-Bechal S, Smales FC: Variance components analysis of data from periodontal research. Journal of periodontal research 1988, 23(2):148-153.
Albandar JM, Goldstein H: Multi-level statistical models in studies of periodontal diseases. Journal of periodontology 1992, 63(8):690-695.
Vettore MV, Marques RA, Peres MA: [Social inequalities and periodontal disease: multilevel approach in SBBrasil 2010 survey]. Revista de saude publica 2013, 47 Suppl 3:29-39.
Gilthorpe MS, Cunningham SJ: The application of multilevel, multivariate modelling to orthodontic research data. Community dental health 2000, 17(4):236-242.
Gilthorpe MS, Mayhew MT, Bulman JS: Multilevel survival analysis of amalgam restorations amongst RAF personnel. Community dental health 2002, 19(1):3-11.
Shah R, Thomas R, Bhandari S, Mehta DS: Influence of various factors on patient compliance after periodontal therapy: A pilot study. Journal of Indian Society of Periodontology 2017, 21(1):50-54.
Tomasi C, Leyland AH, Wennstrom JL: Factors influencing the outcome of non-surgical periodontal treatment: a multilevel approach. Journal of clinical periodontology 2007, 34(8):682-690.
D'Aiuto F, Ready D, Parkar M, Tonetti MS: Relative contribution of patient-, tooth-, and site-associated variability on the clinical outcomes of subgingival debridement. I. Probing depths. Journal of periodontology 2005, 76(3):398-405.
Caffesse RG, Sweeney PL, Smith BA: Scaling and root planing with and without periodontal flap surgery. Journal of clinical periodontology 1986, 13(3):205-210.
Shi SW, Meng Y, Jiao J, Li WJ, Meng HX, Luan QX, Wang WC: [Tooth loss and multivariable analysis after 5-year non-surgical periodontal treatment on molars with furcation involvement]. Beijing da xue xue bao Yi xue ban = Journal of Peking University Health sciences 2019, 51(5):913-918.
Angst PD, Piccinin FB, Oppermann RV, Marcantonio RA, Gomes SC: Response of molars and non-molars to a strict supragingival control in periodontal patients. Brazilian oral research 2013, 27(1):55-60.
Dietrich T, Walter C, Oluwagbemigun K, Bergmann M, Pischon T, Pischon N, Boeing H: Smoking, Smoking Cessation, and Risk of Tooth Loss: The EPIC-Potsdam Study. Journal of dental research 2015, 94(10):1369-1375.
Bunaes DF, Lie SA, Enersen M, Aastrom AN, Mustafa K, Leknes KN: Site-specific treatment outcome in smokers following non-surgical and surgical periodontal therapy. Journal of clinical periodontology 2015, 42(10):933-942.
Feres M, Bernal M, Matarazzo F, Faveri M, Duarte PM, Figueiredo LC: Subgingival bacterial recolonization after scaling and root planing in smokers with chronic periodontitis. Australian dental journal 2015, 60(2):225-232.
Lee CT, Huang HY, Sun TC, Karimbux N: Impact of Patient Compliance on Tooth Loss during Supportive Periodontal Therapy: A Systematic Review and Meta-analysis. Journal of dental research 2015, 94(6):777-786.
Robinson DP, Hall OJ, Nilles TL, Bream JH, Klein SL: 17beta-estradiol protects females against influenza by recruiting neutrophils and increasing virus-specific CD8 T cell responses in the lungs. Journal of virology 2014, 88(9):4711-4720.
Furuta M, Shimazaki Y, Tanaka S, Takeuchi K, Shibata Y, Takeshita T, Nishimura F, Yamashita Y: Gender-specific associations of serum antibody to Porphyromonas gingivalis and inflammatory markers. BioMed research international 2015, 2015:897971.
Russell SL, Gordon S, Lukacs JR, Kaste LM: Sex/Gender differences in tooth loss and edentulism: historical perspectives, biological factors, and sociologic reasons. Dental clinics of North America 2013, 57(2):317-337.

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published 01 Jun, 2021

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Editorial decision: Major revision
23 Nov, 2020
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30 Sep, 2020
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Reviewers invited by journal
13 May, 2020
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Prognostic factors affecting the short-term efficacy of non-surgical treatment of chronic periodontitis: a multilevel modelling analysis

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Abstract

Figures

Background

Materials And Methods

Patients

Clinical data collection

Statistical analysis

Results

Demographic data and variables assignment

Description and comparison of PD at different sites before and after treatment

Multi-level modeling analysis

Discussion

Conclusions

Abbreviations

Declarations

References

Status:

Journal Publication

Version 1