Clinical Prediction Rule for Bacteremia Among Patients with Pyelonephritis and Hospitalization Judgment: Chi-Squared Automatic Interaction Detector (CHAID) Decision Tree Analysis Model

Abstract Background: Positive risk factors for bacteremia among patients with pyelonephritis have not been defined using a Chi-Squared Automatic Interaction Detector (CHAID) Decision Tree Analysis Model. Purpose: We sought to identify predictive factors for bacteremia among patients with pyelonephritis and therefore which patients need hospitalization.Methods: This retrospective cross-sectional survey was performed at the Juntendo University Nerima Hospital, Tokyo, Japan and comprised all patients with pyelonephritis from whom blood cultures were taken from January 1, 2010 to July 31, 2020. At the time of blood culture sample collection, clinical information was obtained from medical charts, along with vital signs, quick Sequential Organ Failure Assessment (qSOFA), subjective symptoms, objective physical findings, laboratory findings, and results of blood and urine cultures. Factors potentially predictive of bacteremia among patients with pyelonephritis were analyzed using the Student’s t-test or chi-squared test and the CHAID decision tree analysis model.Results: A total of 198 patients (male:female, 60 (30.3%):138 (69.7%), ages (mean±SD) 74.69±15.27 years) were included in this study, of whom 92 (46.4%) had positive blood culture results. The CHAID decision tree analysis revealed that patients with White blood cell >21,000/μL had a quite-high-risk (89.5%) of developing bacteremia. Patients with White blood cell ≤21,000/μL plus Chill plus Aspartate aminotransferase >19 IU/L represented a high-risk group (69.0%). Conversely, patients with White blood cell ≤21,000/μL plus non-Chill plus Albumin >3.60 g/dL were at a low risk (16.3%) of developing bacteremia.Conclusion: Our results emphasize the importance of hospitalization among high-risk and quite-high-risk groups of pyelonephritis patients.