ArticleJournal of periodontal research2017
Cross-talk between clinical and host-response parameters of periodontitis in smokers.
Article in Journal of periodontal research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- The association between periodontal disease and lung cancer: a re-evaluation of independent causal relationships in the presence of smoking as a confounder and an exploration of potential mechanisms.Frontiers in cellular and infection microbiology · 2026Review
- Article
- [Correlation between cigarette smoking and periodontal status: A survey on the population of a community above 35-year-old in Beijing].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2019Article
- Smoking and periodontal microorganisms.The Japanese dental science review · 2019Review
- Ageing effects on humoral immune responses in chronic periodontitis.Journal of clinical periodontology · 2018Article
- Integrated biomarker profiling of smokers with periodontitis.Journal of clinical periodontology · 2017Article
- The influence ofCentral-European journal of immunology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
objectivePeriodontal diseases are a major public health concern leading to tooth loss and have also been shown to be associated with several chronic systemic diseases. Smoking is a major risk factor for the development of numerous systemic diseases, as well as periodontitis. While it is clear that smokers have a significantly enhanced risk for developing periodontitis leading to tooth loss, the population varies regarding susceptibility to disease associated with smoking. This investigation focused on identifying differences in four broad sets of variables, consisting of: (i) host-response molecules; (ii) periodontal clinical parameters; (iii) antibody responses to periodontal pathogens and oral commensal bacteria; and (iv) other variables of interest, in a population of smokers with (n = 171) and without (n = 117) periodontitis. MATERIAL AND
methodsBayesian network structured learning (BNSL) techniques were used to investigate potential associations and cross-talk between the four broad sets of variables.
resultsBNSL revealed two broad communities with markedly different topology between the populations of smokers, with and without periodontitis. Confidence of the edges in the resulting network also showed marked variations within and between the periodontitis and nonperiodontitis groups.
conclusionThe results presented validated known associations and discovered new ones with minimal precedence that may warrant further investigation and novel hypothesis generation. Cross-talk between the clinical variables and antibody profiles of bacteria were especially pronounced in the case of periodontitis and were mediated by the antibody response profile to Porphyromonas gingivalis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.