MétaCan
Menu
Back to cohort
Record W7124859000 · doi:10.70082/c84q3h57

The Contribution Of Pharmacists To Antibiotic Stewardship In Dental Practice: A Systematic Review

2024· article· W7124859000 on OpenAlexaboutno aff
Ahmed Nashi Rashed Alnashi

Bibliographic record

VenueThe Review of Diabetic Studies · 2024
Typearticle
Language
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsAntimicrobial stewardshipObservational studyPsychological interventionSystematic reviewGuidelineMedical prescriptionRandomized controlled trialAntibiotic StewardshipAuditMEDLINE

Abstract

fetched live from OpenAlex

Background: Dental practice is a significant source of outpatient antibiotic prescriptions, contributing substantially to the global challenge of antimicrobial resistance (AMR). A considerable proportion of these prescriptions are inconsistent with evidence-based guidelines. Pharmacist-led antimicrobial stewardship (AMS) programs have demonstrated efficacy in other healthcare settings, but their specific contribution within dentistry is less synthesized. This systematic review aims to evaluate the role, interventions, and impact of pharmacists in promoting appropriate antibiotic use in dental practice. Objectives: To systematically review and synthesize the available evidence regarding the role and effectiveness of pharmacists and pharmacist-led interventions in dental antibiotic stewardship. Methods: A systematic search of electronic databases was conducted to identify studies evaluating pharmacist-led AMS interventions in dental settings. The review included randomized controlled trials (RCTs), non-randomized controlled trials, and observational studies. Data on study design, intervention components, and outcomes related to antibiotic prescribing were extracted and synthesized narratively. The methodological quality of included studies was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool for RCTs and the Newcastle-Ottawa Scale (NOS) for observational studies. Key Findings: The evidence consistently demonstrates that pharmacist-led interventions are highly effective in improving antibiotic prescribing in dentistry. These interventions, which include educational outreach, academic detailing, audit and feedback, and collaborative guideline development, have been shown to reduce inappropriate antibiotic prescribing by approximately 70%. Pharmacists contribute essential expertise in pharmacotherapy, antibiotic spectra, and resistance patterns, filling a critical knowledge gap for many dental practitioners. Successful programs are characterized by interprofessional collaboration, institutional commitment, and data-driven feedback mechanisms. However, significant systemic barriers, including professional siloing, inadequate communication channels, educational deficiencies in dental curricula, and a lack of integrated health information systems, hinder the widespread implementation of these effective collaborations. Conclusions: There is compelling evidence that pharmacists are a critical and currently underutilized resource in advancing antibiotic stewardship in dental practice. Their involvement leads to substantial and clinically meaningful improvements in prescribing appropriateness. To fully realize this potential, systemic changes are required, including the integration of interprofessional AMS education into dental and pharmacy curricula, the development of supportive health policies and reimbursement models, and the adoption of technologies that facilitate seamless collaboration.

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)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.009
Bibliometrics0.0100.011
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
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 head0.017
GPT teacher head0.365
Teacher spread0.348 · 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 designSystematic review
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Review of Diabetic StudiesSame topicAntibiotic Use and ResistanceFrench-language works237,207