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Table 5 Logistic regression analyses on the association of increased workload with a study’s research area and impact factor of the journal in which the study was published, for a non-academic general teaching hospital

From: Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence

Variable Univariate analysis Multivariate analysis
OR 95% CI p value OR 95% CI p value
Study’s research areaa 11.05b 3.39–36.01b  < 0.001b 10.45b 3.19–34.21b  < 0.001b
Impact factor of the journal in which the study was publishedc 0.94d 0.87–1.01d 0.065 0.950d 0.87–1.04d 0.268
  1. CI: confidence interval, OR: odds ratio
  2. aBased on 277 studies with the following primary research areas: artificial intelligence (n = 37), breast (n = 16), cardiac (n = 32), chest (n = 18), computed tomography (n = 4), emergency (n = 1), gastrointestinal–abdominal (n = 20), head–neck (n = 6), magnetic resonance (n = 3), multisystem (n = 1), musculoskeletal (n = 18), neuroradiology (n = 44), nuclear medicine (n = 50), oncology (n = 1), pediatric (n = 2), ultrasonography (n = 2), urogenital (n = 17), and vascular (n = 5)
  3. bStudies with artificial intelligence as research area were significantly associated with increased workload
  4. cBased on 25 individual journals with a median impact factor of 4.966 (range 2.687–33.752)
  5. dPer unit increase in impact factor