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Record W2611591534 · doi:10.1080/16549716.2017.1287334

Antibiotic prescribing for upper respiratory infections among children in rural China: a cross-sectional study of outpatient prescriptions

2017· article· en· W2611591534 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Health Action · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersDepartment for International DevelopmentDepartment for International Development, UK Government
KeywordsMedicineMedical prescriptionAntibioticsCross-sectional studyLogistic regressionOdds ratioHealth facilityPediatricsEnvironmental healthInternal medicineHealth servicesPopulationNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Overuse of antibiotics contributes to the development of antimicrobial resistance. OBJECTIVE: This study aims to assess the condition of antibiotic use at health facilities at county, township and village levels in rural Guangxi, China. METHODS: We conducted a cross-sectional study of outpatient antibiotic prescriptions in 2014 for children aged 2-14 years with upper respiratory infections (URI). Twenty health facilities were randomly selected, including four county hospitals, eight township hospitals and eight village clinics. Prescriptions were extracted from the electronic records in the county hospitals and paper copies in the township hospitals and village clinics. RESULTS: The antibiotic prescription rate was higher in township hospitals (593/877, 68%) compared to county hospitals (2736/8166, 34%) and village clinics (96/297, 32%) (p < 0.001). Among prescriptions containing antibiotics, county hospitals were found to have the highest use rate of broad-spectrum antibiotics (82 vs 57% [township], vs 54% [village], p < 0.001), injectable antibiotics (65 vs 43% [township], vs 33% [village], p < 0.001) and multiple antibiotics (47 vs 15% [township], vs 0% [village], p < 0.001). Logistic regression showed that the likelihood of prescribing an antibiotic was significantly associated with patients being 6-14 years old compared with being 2-5 years old (adjusted odds ratio [aOR] = 1.3, 95% CI 1.2-1.5), and receiving care at township hospitals compared with county hospitals (aOR = 5.0, 95% CI 4.1-6.0). Prescriptions with insurance copayment appeared to lower the risk of prescribing antibiotics compared with those without (aOR = 0.8, 95% CI 0.7-0.9). CONCLUSIONS: Inappropriate use of antibiotics was high for outpatient childhood URI in the four counties of Guangxi, China, with the highest rate found in township hospitals. A significant high proportion of prescriptions containing antibiotics were broad-spectrum, by intravenous infusion or with multiple antibiotics, especially at county hospitals. Urgent attention is needed to address this challenge.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.354
Teacher spread0.323 · 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