{
  "abstract": "Recurrent acute otitis media (rAOM; defined as ≥3 AOM episodes in 6 months or ≥4 episodes in 12 months) affects 10–15% of children in the United States and is a leading cause of healthcare utilization and antibiotic prescriptions. Prospective identification of children at risk of rAOM could help target interventions and identify new risk factors to guide preventive approaches. We therefore sought to develop predictive models to identify children at risk of rAOM using electronic health records (EHR) data. We extracted retrospective EHR data for children who were born at Duke University Health System (DUHS) hospitals between January 1, 2014, and June 30, 2022, and who had at least one AOM episode during the study period. We used LASSO to build predictive models for development of rAOM at each episode and identified factors associated with rAOM. We identified 6,566 children who met the study criteria, including 1,634 (24.8%) who met criteria for rAOM. A model using only data available at the first AOM episode had an area under the curve (AUC) of 0.75 (0.73, 0.77) and an Area Under the Precision Recall Curve (AUPRC) of 0.41 (95% CI 0.37, 0.46), indicating moderate discriminative ability. At the time of the first AOM episode, features associated with subsequent rAOM development included age, number of prior antibiotic prescriptions, and diagnosis of gastroesophageal reflux disease (GERD). Further, children who developed rAOM were more likely to experience treatment failure than children who did not meet rAOM criteria across all episodes. Our findings indicate that clinical exposures and patient characteristics documented in the EHR distinguish children who are at risk of developing rAOM. Such models could be deployed within EHR systems to identify children who would benefit from early evaluation by an otolaryngologist and audiologist.",
  "abstract_shown": true,
  "affiliations": [
    "Division of Infectious Diseases, Department of Pediatrics, Duke University School of Medicine, Durham, North Carolina, United States of America",
    "Department of Pediatrics, Children’s Health and Discovery Initiative, Duke University School of Medicine, Durham, North Carolina, United States of America",
    "Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America",
    "Department of Head and Neck Surgery & Communication Sciences, Duke University School of Medicine, Durham, North Carolina, United States of America",
    "Department of Pediatric Otolaryngology-Head and Neck Surgery, Children’s Hospital Colorado, Aurora, Colorado, United States of America",
    "Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America",
    "Section of Infectious Diseases, Durham Veterans Affairs Healthcare System, Durham, North Carolina, United States of America",
    "Duke Clinical Research Institute, Duke University, Durham, North Carolina, United States of America",
    "Section of Infectious Diseases, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jillian H. Hurst"
    },
    {
      "affs": [
        1
      ],
      "name": "Congwen Zhao"
    },
    {
      "affs": [
        2
      ],
      "name": "Eileen M. Raynor"
    },
    {
      "affs": [
        3
      ],
      "name": "Janet W. Lee"
    },
    {
      "affs": [
        4
      ],
      "name": "Sarah A. Gitomer"
    },
    {
      "affs": [
        5
      ],
      "name": "Christopher W. Woods"
    },
    {
      "affs": [
        6
      ],
      "name": "Matthew S. Kelly"
    },
    {
      "affs": [
        7
      ],
      "name": "Michael J. Smith"
    },
    {
      "affs": [
        8
      ],
      "name": "Benjamin A. Goldstein"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dfjfqsrzgjtdy.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0345434",
  "fulltext_url": null,
  "id": "dfjfqsrzgjtdy",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0345434",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2733|Ear Surgery and Otitis Media"
    ],
    [
      "plos",
      "/Biology and life sciences/Microbiology/Microbial control/Antimicrobials/Antibiotics"
    ],
    [
      "plos",
      "/Computer and information sciences/Information technology/Health information technology/Electronic medical records"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Gastroenterology and hepatology/Gastroesophageal reflux disease"
    ],
    [
      "plos",
      "/Medicine and health sciences/Health care/Health information technology/Electronic medical records"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Infectious diseases/Infectious disease control/Vaccines/Conjugate vaccines"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pediatrics/Child health"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pharmacology/Drugs/Antimicrobials/Antibiotics"
    ],
    [
      "plos",
      "/Medicine and health sciences/Public and occupational health/Child health"
    ],
    [
      "plos",
      "/Medicine and health sciences/Women's health/Maternal health/Birth/Labor and delivery"
    ],
    [
      "plos",
      "/Medicine and health sciences/Women's health/Obstetrics and gynecology/Birth/Labor and delivery"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Forecasting"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Forecasting"
    ]
  ],
  "openalex": "W7213535588",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0345434&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/dfjfqsrzgjtdy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0345434",
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      "url": "https://doi.org/10.1371/journal.pone.0345434"
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  "subjects": [
    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
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    {
      "field": "medicine",
      "origin": "plos:epidemiology",
      "subfield": "epidemiology-public-health"
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    {
      "field": "medicine",
      "origin": "plos:pediatrics",
      "subfield": "reproductive-child"
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  ],
  "title": "Early life factors documented in electronic health records predict recurrent acute otitis media",
  "title_text": "Early life factors documented in electronic health records predict recurrent acute otitis media",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/dfjfqsrzgjtdy",
  "venue": "PLOS One",
  "versions": []
}