Background In older adults, the diagnosis of acute pyelonephritis is challenging because of non-specific symptoms and false-positive urine test results. Few studies have investigated the diagnostic performance of computed tomography (CT) signs. Purpose To evaluate the diagnostic performance of CT signs for acute pyelonephritis in older patients suspected of infection with unknown focus. Material and Methods This cross-sectional study was conducted between 2015 and 2018. Patients aged ≥65 years who underwent blood cultures, urine culture, and non-contrast or contrast-enhanced CT on admission were included. Cases with clinically presumable infection focus before CT were excluded. Two radiologists blinded to clinical information independently reviewed five CT signs: perirenal fat stranding; pelvicalyceal wall thickening and enhancement; renal enlargement; thickening of Gerota’s fascia; and area(s) of decreased attenuation. The final diagnoses were made by a clinical expert panel. Results Among 473 eligible patients, 61 were diagnosed with acute pyelonephritis. When the laterality of findings between the left and right kidneys were considered, the positive and negative likelihood ratios of perirenal fat stranding were 4.0 (95% confidence interval [CI] = 2.3–7.0) and 0.8 (95% CI = 0.7–0.9) in non-contrast CT, respectively. The other signs in non-contrast CT showed similar diagnostic performance with positive and negative likelihood ratios of 3.5–11.3 and 0.8–0.9, respectively. Conclusion CT signs can help physicians diagnose acute pyelonephritis in older patients suspected of infection with unknown focus.

To evaluate the added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection. Methods: This study was conducted at an acute care hospital (471-bed capacity). Consecutive adult patients suspected of severe infection who presented to either ambulatory care or the emergency department from April 2015 to March 2017 were retrospectively evaluated. A prognostic model for predicting 30-day inhospital mortality based on previously established vital signs (systolic blood pressure, respiratory rate, and mental status) was compared with an extended model that also included four inflammatory markers (C-reactive protein, neutrophil-lymphocyte ratio, mean platelet volume, and red cell distribution width). Measures of interest were model fit, discrimination, and the net percentage of correctly reclassified individuals at the pre-specified threshold of 10% risk. Results: Of the 1015 patients included, 66 (6.5%) died. The extended model including inflammatory markers performed significantly better than the vital sign model (likelihood ratio test: p b 0.001), and the c-index increased from 0.69 (range 0.67-0.70) to 0.76 (range 0.75-0.77) (p = 0.01). All included markers except C-reactive protein showed significant contribution to the model improvement. Among those who died, 9.1% (95% CI −2.8-21.8) were correctly reclassified by the extended model at the 10% threshold. Conclusions: The inflammatory markers except C-reactive protein showed added predictive value to vital signs. Future studies should focus on developing and validating prediction models for use in individualized predictions including both vital signs and the significant markers.