ArticleBMC infectious diseases2016
Classification and Regression Tree (CART) analysis to predict influenza in primary care patients.
Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.
- Pooled it
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- Safety and outcome of elective synthetic mesh repair for incisional ventral hernias in immunosuppressed patients - a retrospective propensity-score-matched analysis.Hernia : the journal of hernias and abdominal wall surgery · 2025Article
- Methodologies for the collection of parameters to estimate dust/soil ingestion for young children.Frontiers in public health · 2024Article
- Integrated Machine Learning Decision Tree Model for Risk Evaluation in Patients with Non-Valvular Atrial Fibrillation When Taking Different Doses of Dabigatran.International journal of environmental research and public health · 2023Article
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- Risk factors for pressure ulcer recurrence following surgical reconstruction: A cross-sectional retrospective analysis.Frontiers in surgery · 2023Article
- Predicting the COVID-19 Patients Status Using Chest CT Scan Findings: A Risk Assessment Model Based on Decision Tree Analysis.Advances in experimental medicine and biology · 2023Article
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- Simple clinical and laboratory predictors to improve empirical treatment strategies in areas of high scrub typhus and dengue endemicity, central Vietnam.PLoS neglected tropical diseases · 2022Article
- Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach.Journal of medical Internet research · 2022Article
- A technology-based information and coaching/support program and self-efficacy of Asian American breast cancer survivors.Research in nursing & health · 2021Article
- Patient Risk Factor Profiles Associated With the Timing of Goals-of-Care Consultation Before Death: A Classification and Regression Tree Analysis.The American journal of hospice & palliative care · 2020Observational
- Item reduction of the 39-item Rotterdam Diabetic Foot Study Test Battery using decision tree modelling.Diabetes/metabolism research and reviews · 2020Article
- Classification and Regression Tree and Computer Adaptive Testing in Cardiac Rehabilitation: Instrument Validation Study.Journal of medical Internet research · 2020Article
- Differentiation between pilocytic astrocytoma and glioblastoma: a decision tree model using contrast-enhanced magnetic resonance imaging-derived quantitative radiomic features.European radiology · 2019Article
- Identification of Pancreatic Injury in Patients with Elevated Amylase or Lipase Level Using a Decision Tree Classifier: A Cross-Sectional Retrospective Analysis in a Level I Trauma Center.International journal of environmental research and public health · 2018Article
- Article
Corrections and comments
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Authors and funding
15 authors at 7 institutions in 1 country.
Funding
Abstract
backgroundThe use of neuraminidase-inhibiting anti-viral medication to treat influenza is relatively infrequent. Rapid, cost-effective methods for diagnosing influenza are needed to enable appropriate prescribing. Multi-viral respiratory panels using reverse transcription polymerase chain reaction (PCR) assays to diagnose influenza are accurate but expensive and more time-consuming than low sensitivity rapid influenza tests. Influenza clinical decision algorithms are both rapid and inexpensive, but most are based on regression analyses that do not account for higher order interactions. This study used classification and regression trees (CART) modeling to estimate probabilities of influenza.
methodsEligible enrollees ≥ 5 years old (n = 4,173) who presented at ambulatory centers for treatment of acute respiratory illness (≤7 days) with cough or fever in 2011-2012, provided nasal and pharyngeal swabs for PCR testing for influenza, information on demographics, symptoms, personal characteristics and self-reported influenza vaccination status.
resultsAntiviral medication was prescribed for just 15 % of those with PCR-confirmed influenza. An algorithm that included fever, cough, and fatigue had sensitivity of 84 %, specificity of 48 %, positive predictive value (PPV) of 23 % and negative predictive value (NPV) of 94 % for the development sample.
conclusionsThe CART algorithm has good sensitivity and high NPV, but low PPV for identifying influenza among outpatients ≥5 years. Thus, it is good at identifying a group who do not need testing or antivirals and had fair to good predictive performance for influenza. Further testing of the algorithm in other influenza seasons would help to optimize decisions for lab testing or treatment.
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Registered trials
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.