Clinical prediction rule for bacterial arthritis: Chi-squared automatic interaction detector decision tree analysis model.

Objectives: Differences in demographic factors, symptoms, and laboratory data between bacterial and non-bacterial arthritis have not been defined. We aimed to identify predictors of bacterial arthritis, excluding synovial testing. Methods: This retrospective cross-sectional survey was performed at a university hospital. All patients included received arthrocentesis from January 1, 2010, to December 31, 2020. Clinical information was gathered from medical charts from the time of synovial fluid sample collection. Factors potentially predictive of bacterial arthritis were analyzed using the Student's t-test or chi-squared test, and the chi-squared automatic interaction detector decision tree analysis. The resulting subgroups were divided into three groups according to the risk of bacterial arthritis: low-risk, intermediate-risk, or high-risk groups. Results: A total of 460 patients (male/female = 229/231; mean ± standard deviation age, 70.26 ± 17.66 years) were included, of whom 68 patients (14.8%) had bacterial arthritis. The chi-squared automatic interaction detector decision tree analysis revealed that patients with C-reactive protein > 21.09 mg/dL (incidence of septic arthritis: 48.7%) and C-reactive protein ⩽ 21.09 mg/dL plus 27.70 < platelet count ⩽ 30.70 × 104/µL (incidence: 36.1%) were high-risk groups. Conclusions: Our results emphasize that patients categorized as high risk of bacterial arthritis, and appropriate treatment could be initiated as soon as possible.

Comparison of the clinical parameters of patients with COVID-19 and influenza using blood test data: a retrospective cross-sectional survey.

OBJECTIVE: The characteristic features, including blood test data, of the novel coronavirus disease 2019 (COVID-19) versus influenza have not been defined. We therefore compared the clinical parameters, including blood test data, of COVID-19 and influenza. METHODS: This retrospective cross-sectional survey was conducted at Juntendo University Nerima Hospital. We recruited patients diagnosed with COVID-19 between 1 January 2020 and 31 December 2020 who underwent blood tests. For comparison, we recruited an equivalent number of patients who were diagnosed with influenza and who underwent blood tests. RESULTS: During the study period, 228 patients (male:female, 123 [54.0%]:105 [46.0%]; age, 54.68 ± 18.98 years) were diagnosed with COVID-19. We also recruited 228 patients with influenza (male:female, 129 [56.6%]:99 [43.4%]; age, 69.6 ± 21.25 years). An age of 15 to 70 years (vs. 71 years), breathing difficulty, and malaise were significantly more common in patients with COVID-19 than in those with influenza. However, nausea, body temperature >38.1°C, and white blood cell count >9000/µL were more common in patients with influenza. CONCLUSIONS: Our results are useful for differentiating COVID-19 from influenza, and these findings will be extremely helpful for future practice as we learn to coexist with COVID-19.