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Record W4389436452 · doi:10.3390/cimb45120614

Retinol-Binding Protein 4 and Visfatin Levels in Patients with Periodontitis and Obesity/Overweight: A Systematic Review and Meta-Analysis

2023· review· en· W4389436452 on OpenAlexaboutno aff
Yuwei Zhang, Ru Jia, Yifei Zhang, Rui Zou, Lin Niu, Shaojie Dong

Bibliographic record

VenueCurrent Issues in Molecular Biology · 2023
Typereview
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineMeta-analysisPeriodontitisConfidence intervalOverweightObesityRetinol binding protein 4Observational studyStrictly standardized mean differenceGastroenterologyAdipokineInsulin resistance

Abstract

fetched live from OpenAlex

Prior studies demonstrated an equivocal conclusion about the association between the level of retinol-binding protein 4 (RBP4)/visfatin and periodontitis patients with obesity. The aim of our study (Prospero ID: CRD42023469058) was to systematically review the available articles linking the biofluid levels of RBP4/visfatin to the comorbidity of periodontitis and obesity. Clinical trials were screened in accordance with specific inclusion criteria from seven databases up to November 2023. A quality assessment was performed with the Newcastle–Ottawa Scale and ROBINS-I tools for observational and interventional trials, respectively. The standard mean difference (SMD) with a 95% confidence interval (CI) related to the RBP4 level was recorded; the other indicators related to the visfatin level were measured via the mean difference (MD) with the corresponding 95% CI, and Fisher’s Z transformation was measured to reveal the association using Review Manager 5.4. The current evidence was based on five observational studies and two interventional studies. All of them were included in the systematic review, and six of them were in the meta-analysis. Statistical analysis indicated that there was no significant difference in the circulating levels of RBP4 in the periodontitis patients with obesity or without, who were labeled as OP or NP, respectively (155 OP-107 NP: SMD = 1.38; 95% CI: −0.18–2.94, p = 0.08), as well as the periodontal healthy patients with a normal weight, who were labelled as NnP (116 OP-79 NnP: SMD = 6.76; 95% CI: −5.34–18.87, p = 0.27). Meanwhile, a significant higher level of serum visfatin was found in the OP patients than that of the NP (86 OP-45 NP: MD = 4.21; 95% CI: 2.65–5.77, p < 0.00001)/NnP (164 OP-88 NnP: MD = 13.02; 95% CI: 7.34–18.70, p < 0.00001) group. In addition, a positive association was observed between the serum RBP4 and body mass index/clinical attachment loss (CAL). And, then, there was a positive association between the serum visfatin and periodontal parameters, including the probing depth, CAL, and plaque index, as well as metabolic parameters, including the total cholesterol, triglycerides, fasting blood glucose, and low-density lipoprotein cholesterol. Here, the circulating RBP4 level was not independently related to the comorbidity of periodontitis and obesity, while serum visfatin was significantly associated with periodontitis and obesity. Notably, the positive association between circulating RBP4/visfatin and the periodontal parameters/metabolic parameters firmly suggested that the higher severity of the obese or periodontal status was associated with an elevated level of serum visfatin or RBP4 in the OP group. With more rigorous longitudinal research, the exact causations between RBP4/visfatin and the patients affected by obesity and periodontitis could be disentangled. RBP4 and visfatin might be novel, enlightening prospective bio-indexes for the targeted treatment of comorbidities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.026
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.035
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.403
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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