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Record W4399652885 · doi:10.3389/jpps.2024.12721

Community pharmacists as antimicrobial resistance stewards: a narrative review on their contributions and challenges in low- and middle-income countries

2024· review· en· W4399652885 on OpenAlexvenueno aff
Rosy Raju, Sunitha Chandrashekar Srinivas, Srikanth Malavalli Siddalingegowda, R. U. Vaidya, Manjiri Gharat, T. M. Pramod Kumar

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2024
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsnot available
FundersJSS Academy of Higher Education and ResearchPfizer
KeywordsAntimicrobial stewardshipStewardship (theology)Low and middle income countriesHealth careTransformational leadershipMedicineResistance (ecology)Public relationsPopulationPublic healthNursingAntibiotic resistanceBusinessPolitical scienceDeveloping countryEconomic growthEnvironmental healthPolitics

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) is a global public health crisis that impedes the therapeutic effectiveness of available antimicrobial agents. Due to the high burden of infectious diseases and limited resources, especially trained healthcare professionals, low- and middle-income countries (LMICs) are particularly susceptible to the detrimental effects of AMR. Sometimes, as the first and last point of contact for patients seeking treatment for infections, community pharmacists can play a pivotal role in the stewardship required for AMR. This review aims to highlight the contributions made by community pharmacists in LMICs as AMR stewards. The review considers the challenges from the perspectives of limited resources, inadequate training, a lack of policies and regulations, and issues related to patient behavior. Community pharmacists in LMICs could optimize their advocacy contributions by focusing on One Health AMR stewardship. Transformational and actionable patient and population-centric antimicrobial stewardship (AMS) is feasible with the synergy of policymakers and other healthcare providers in the implementation of AMS policies and programs that support community pharmacists in their efforts to promote rational antimicrobial use.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.143
GPT teacher head0.435
Teacher spread0.291 · 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 teacher head, not a consensus.

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

Citations19
Published2024
Admission routes1
Has abstractyes

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