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An external validation study of a clinical prediction rule for medical patients with suspected bacteraemia
  1. Luke Eliot Hodgson1,
  2. Nicholas Dragolea2,
  3. Richard Venn1,
  4. Borislav D Dimitrov3,
  5. Lui G Forni4
  1. 1Intensive Care Department, Western Sussex Hospitals NHS Foundation Trust, Worthing Hospital, Worthing, West Sussex, UK
  2. 2Brighton and Sussex Medical School, Royal Sussex County Hospital, Brighton, East Sussex, UK
  3. 3Primary Care and Population Sciences, University of Southampton, Southampton General Hospital, Southampton, Hampshire, UK
  4. 4Intensive Care Department, The Royal Surrey County Hospital NHS Foundation Trust, Guildford, Surrey, UK
  1. Correspondence to Dr Luke Eliot Hodgson, Intensive Care Department, Western Sussex Hospitals NHS Foundation Trust, Worthing Hospital, Lyndhurst Rd, Worthing, West Sussex BN11 2DH, UK; drlhodgson{at}


Objective The objective of this study was to externally validate a clinical prediction rule (CPR)—the ‘Shapiro criteria’—to predict bacteraemia in an acute medical unit (AMU).

Methods Prospectively collected data, retrospectively evaluated over 11 months in an AMU in the UK. From 4810 admissions, 635 patients (13%) had blood cultures (BCs) performed. The 100 cases of true bacteraemia were compared with a randomly selected sample of 100 control cases where BCs were sterile.

Results To predict bacteraemia (at a cut-off score of two points), the Shapiro criteria had a sensitivity of 97% (95% CIs 91% to 99%), specificity 37% (28% to 47%), positive likelihood ratio 1.54 (1.3 to 1.8) and a negative likelihood ratio of 0.08 (0.03 to 0.25). The area under the receiver operating curve was 0.80 (0.74 to 0.86), and the Hosmer–Lemeshow p value was 0.45.

Conclusions A cut-off score of two points on the Shapiro criteria had high sensitivity to predict bacteraemia in a study of acute general medical admissions. Application of the rule in patients being considered for a BC could identify those at low risk of bacteraemia. Though the model demonstrated good discrimination, the lengthy number of variables (13) and difficulty automating the CPR may limit its use.

  • infectious diseases
  • bacterial

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