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      Molecular biomarkers for objective assessment of symptomatic pulpitis: A systematic review and meta‐analysis

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          Abstract

          Background

          Inflammatory biomarkers are potentially useful targets for pulpal diagnostic tests that can identify pulp status and predict vital pulp treatment (VPT) outcome, however, their accuracy is unknown.

          Objectives

          (1) Calculate sensitivity, specificity and diagnostic odds ratio (DOR) of previously investigated pulpitic biomarkers; (2) Determine if biomarker levels discriminate between clinical diagnoses of pulpitis based on the presence or absence of spontaneous pain (3) Evaluate if biomarker level can predict VPT outcome.

          Methods

          Searches: PubMed/MEDLINE, Ovid SP, Cochrane Central Register of Controlled Trials (CENTRAL), International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov, Embase, Web of Science and Scopus in May 2023. Inclusion: prospective and retrospective observational studies and randomized trials. Participants were humans with vital permanent teeth and a well‐defined pulpal diagnosis. Exclusion: deciduous teeth, in vitro and animal studies. Risk of bias was assessed with modified‐Downs and Black quality assessment checklist. Meta‐analysis was performed using bivariate random effect model in Meta‐DiSc 2.0 and RevMan and the quality of the evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation.

          Results

          Fifty‐six studies were selected, reporting >70 individual biomolecules investigating pulpal health and disease at the gene and protein level. Most studies were of low and fair quality. Among the biomolecules investigated, IL‐8 and IL‐6 demonstrated a level of diagnostic accuracy with high sensitivity, specificity and DOR to discriminate between healthy pulps and those exhibiting spontaneous pain suggestive of IRP (low‐certainty evidence). However, none was shown to have high DOR and the ability to discriminate between pulpitic states (very low certainty evidence). Limited data suggests high levels of matrix metalloproteinase 9 correlate with poorer outcomes of full pulpotomy.

          Discussion

          The inability of identified molecular inflammatory markers to discriminate between dental pulps with spontaneous and non‐spontaneous pain should shift the focus to improved study quality or the pursuit of other molecules potentially associated with healing and repair.

          Conclusions

          Low‐quality evidence suggests IL‐8 and IL‐6 demonstrated level of diagnostic accuracy to discriminate between healthy pulps and those exhibiting spontaneous pain. There is a need for standardized biomarker diagnostic and prognostic studies focusing on solutions that can accurately determine the degree of pulp inflammation.

          Registration

          PROSPERO CRD42021259305.

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          Most cited references90

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.

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              Estimating the mean and variance from the median, range, and the size of a sample

              Background Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. Methods In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. Results We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n ≤ 15). For moderately sized samples (15 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. Conclusion Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.
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                Author and article information

                Contributors
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                Journal
                International Endodontic Journal
                Int Endodontic J
                Wiley
                0143-2885
                1365-2591
                October 2023
                July 17 2023
                October 2023
                : 56
                : 10
                : 1160-1177
                Affiliations
                [1 ] Faculty of Dentistry University of Khartoum Khartoum Sudan
                [2 ] School of Medicine Dentistry and Biomedical Sciences Queen's University Belfast Belfast UK
                [3 ] Division of Restorative Dentistry & Periodontology Dublin Dental University Hospital, Trinity College Dublin, University of Dublin Dublin Ireland
                Article
                10.1111/iej.13950
                f4607c9e-08d3-4311-a5b9-73dd087e5bb5
                © 2023

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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