Evidence map›Paper›PMID 28915872›Full record

ArticleBMC medical informatics and decision making2017

Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.

J Song, H Zhao, C Pan, C Li, J Liu, Y Pan

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

J SongDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China.
H ZhaoDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China.
C PanDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China.
C LiDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China.
J LiuDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China.
Y PanDepartment of Periodontics and Oral Biology, School of Stomatology, China Medical University, Shenyang, 110002, China. yppan@cmu.edu.cn.ORCID http://orcid.org/0000-0001-8891-6360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting.

methodsFifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters.

resultsCompared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P < 0.001), thus establishing that MLM data analysis was necessary. Site-level had effects on PD and CAL reduction; those variables could explain 77-78% of PD reduction and 70-80% of CAL reduction at 3, 6, and 12 months. Other levels only explain 20-30% of PD and CAL reductions. Site-level had the greatest effect on PD and CAL reduction.

conclusionsNon-surgical periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

Indexed as

Periodontal IndexAdultChinaChronic PeriodontitisFemaleHumansMaleMiddle AgedModels, BiologicalMultilevel AnalysisRisk FactorsWound HealingChronic periodontitisMultilevel modellingPrognosisRisk factors

Identifiers

PMID28915872
PMCPMC5603071

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.