Evidence map›Paper›PMID 41487778›Full record

ArticleCureus2025

Patterns of Antibiotic Prescribing for Pediatric Outpatient Visits in the United States: Findings From the National Ambulatory Medical Care Survey 2010-2015.

Okelue E Okobi, Emmanuel Olawusi, Wuraola R Awosan, Chibuzo N Nwodo, Ifesinachi Nwankwor, Angelina Uzor

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Okelue E OkobiFamily Medicine, Larkin Community Hospital Palm Springs Campus, Miami, USA.
Emmanuel OlawusiPediatrics, Maimonides Medical Center, New York City, USA.
Wuraola R AwosanMedicine, Ternopil National Medical University, Ternopil, UKR.
Chibuzo N NwodoEar, Nose, and Throat (ENT), Royal Derby Hospital, Derby, GBR.
Ifesinachi NwankworGeneral Practice, General Hospital Agulu, Agulu, NGA.
Angelina UzorPublic Health, East Tennessee State University, Johnson City, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInappropriate antibiotic prescribing for children remains a major public health concern, contributing to antimicrobial resistance (AMR), adverse events, and excess healthcare costs. This study examined prescribing patterns in United States (US) pediatric outpatient visits between 2010 and 2015 using the National Ambulatory Medical Care Survey (NAMCS).

methodsWe conducted a cross-sectional analysis of outpatient encounters for patients aged 0-17 years. Antibiotic prescribing was evaluated by diagnosis category, age group, and patient characteristics. Descriptive statistics and adjusted probabilities were generated. Missing data were assessed, with no imputation applied, as most key variables were complete.

resultsAmong 45,666 unweighted pediatric visits, representing 991,561,251 weighted visits, the strongest predictor of antibiotic use was the type of diagnosis. Bacterial infections, particularly otitis media and urinary tract infections, had the highest prescribing probabilities, while non-infectious diagnoses rarely received antibiotics. Respiratory illnesses accounted for substantial prescribing, consistent with prior reports of inappropriate use.  Conclusion: Pediatric antibiotic prescribing during 2010-2015 was primarily diagnosis-driven, with persistent overuse for respiratory conditions. These results underscore the need for strengthened outpatient stewardship strategies to reduce inappropriate use and support guideline-concordant care.

Indexed as

antibiotic stewardshipantimicrobial resistancenamcsoutpatient carepediatricsprescribing patterns

Identifiers

PMID41487778
PMCPMC12756683

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.