A simple scoring algorithm predicting vascular infections in adults with nontyphoid salmonella bacteremia

Po Lin Chen, Ching Chi Lee, Chung Yi Li, Chia Ming Chang, Hsin Chun Lee, Nan Yao Lee, Chi Jung Wu, Hsin I. Shih, Hung Jen Tang, Wen Chien Ko

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Background. Nontyphoid Salmonella (NTS) can cause fatal vascular infections. This study aims to establish a predictive scoring algorithm to identify adults aged ≥50 years with NTS bacteremia who are at risk for vascular infections. Methods. There were 358 adults aged ≥50 years with NTS bacteremia at 2 medical centers in southern Taiwan included in this study. Multiple logistic regression was used to identify risk factors for imaging-documented vascular infections. The prediction capability of the proposed scoring algorithm was indicated by a receiver operating characteristic curve and measures of sensitivity and specificity.Results.Sixty patients (16.8) with vascular infections were noted. The 4 risk factors significantly associated with vascular infections-male sex, hypertension, coronary arterial disease, and serogroup C1 infections-were each assigned +1 point to form the NTS vascular infection (NTSVI) score. In contrast, malignancy and immunosuppressive therapy were each assigned-1 point, owing to their negative associations with vascular infections. Based on the proposed NTSVI scoring, the prevalence of vascular infections in patients with ≤0, 1, 2, 3, or 4 points was 2.2 (3 of 138 patients), 10.6 (13 of 123 patients), 39.4 (26 of 66 patients), 55.2 (16 of 29 patients), and 100 (2 of 2 patients), respectively (P <. 0001). The scoring algorithm shows an area under the curve of 0.83 (95 confidence interval,. 78-.89; P <. 0001). A cutoff value of +1 represents a high sensitivity (95.0) and an acceptable specificity (45.3). Conclusions. This simple scoring algorithm can be used to identify patients with NTS bacteremia with a high risk of vascular infections. The cost-effectiveness of this algorithm should be further studied.

Original languageEnglish
Pages (from-to)194-200
Number of pages7
JournalClinical Infectious Diseases
Volume55
Issue number2
DOIs
Publication statusPublished - 2012 Jul 15

All Science Journal Classification (ASJC) codes

  • Microbiology (medical)
  • Infectious Diseases

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