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Record W2613179329 · doi:10.7326/m16-1131

Antibiotic Prescribing for Nonbacterial Acute Upper Respiratory Infections in Elderly Persons

2017· article· en· W2613179329 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnnals of Internal Medicine · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsMedicineMedical prescriptionRespiratory tract infectionsBronchitisAcute careSinusitisRetrospective cohort studyLogistic regressionAntibioticsCohort studyCohortEmergency medicineInternal medicinePediatricsIntensive care medicineHealth careSurgeryRespiratory system

Abstract

fetched live from OpenAlex

BACKGROUND: Reducing inappropriate antibiotic prescribing for acute upper respiratory tract infections (AURIs) requires a better understanding of the factors associated with this practice. OBJECTIVE: To determine the prevalence of antibiotic prescribing for nonbacterial AURIs and whether prescribing rates varied by physician characteristics. DESIGN: Retrospective analysis of linked administrative health care data. SETTING: Primary care physician practices in Ontario, Canada (January-December 2012). PATIENTS: Patients aged 66 years or older with nonbacterial AURIs. Patients with cancer or immunosuppressive conditions and residents of long-term care homes were excluded. MEASUREMENTS: Antibiotic prescriptions for physician-diagnosed AURIs. A multivariable logistic regression model with generalized estimating equations was used to examine whether prescribing rates varied by physician characteristics, accounting for clustering of patients among physicians and adjusting for patient-level covariates. RESULTS: The cohort included 8990 primary care physicians and 185 014 patients who presented with a nonbacterial AURI, including the common cold (53.4%), acute bronchitis (31.3%), acute sinusitis (13.6%), or acute laryngitis (1.6%). Forty-six percent of patients received an antibiotic prescription; most prescriptions were for broad-spectrum agents (69.9% [95% CI, 69.6% to 70.2%]). Patients were more likely to receive prescriptions from mid- and late-career physicians than early-career physicians (rate difference, 5.1 percentage points [CI, 3.9 to 6.4 percentage points] and 4.6 percentage points [CI, 3.3 to 5.8 percentage points], respectively), from physicians trained outside of Canada or the United States (3.6 percentage points [CI, 2.5 to 4.6 percentage points]), and from physicians who saw 25 to 44 patients per day or 45 or more patients per day than those who saw fewer than 25 patients per day (3.1 percentage points [CI, 2.1 to 4.0 percentage points] and 4.1 percentage points [CI, 2.7 to 5.5 percentage points], respectively). LIMITATION: Physician rationale for prescribing was unknown. CONCLUSION: In this low-risk elderly cohort, 46% of patients with a nonbacterial AURI were prescribed antibiotics. Patients were more likely to receive prescriptions from mid- or late-career physicians with high patient volumes and from physicians who were trained outside of Canada or the United States. PRIMARY FUNDING SOURCE: Ontario Ministry of Health and Long-term Care, Academic Medical Organization of Southwestern Ontario, Schulich School of Medicine and Dentistry, Western University, and Lawson Health Research Institute.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.404

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 studies0.0000.001
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 head0.050
GPT teacher head0.343
Teacher spread0.293 · 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