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The exact negative predictive value of procalcitonin remains to be determined
- Pieter L.J. Degraeuwe (27 October 2009)
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Pieter L.J. Degraeuwe, Consultant Neonatologist Maastricht University Medical Center, Maastricht, The Netherlands
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pde{at}paed.azm.nl Pieter L.J. Degraeuwe
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Dear Sir I am writing this letter in reference to the article "Rapid quantitative procalcitonin measurement to diagnose nosocomial infections in newborn infants" by Jacquot et al. [1] The aim of this study was to investigate the diagnostic accuracy of procalcitonin in neonatal nosocomial infections. However, the flawed methodology and the incomplete reporting preclude a reliable conclusion with respect to the diagnostic performance of procalcitonin for ruling out nosocomial sepsis. With an eye to the study objective, the power calculation should have been based on the expected sensitivity, specificity, predictive accuracy and their minimal acceptable lower confidence limit. [2,3] The authors omitted to report the 95% confidence interval for the estimates of sensitivity and negative predictive value. This prevents the reader of appreciating the range within which the true values are likely to lie [4]. Therefore, I backward calculated the true positive (30), false positive (15), false negative (0), and true negative (28) test results. Using a commercial statistical package (Prism 5.0 GraphPad software, San Diego, CA, USA), the sensitivity (95% CI) can be calculated to be 1 (0.8843 to 1) whereas the accuracy of a negative test is 1 (0.8766 to 1). As yet, given this (im)precision, procalcitonin cannot be used to rule out nosocomial infection in the NICU at the moment of suspicion. References: 1. Jacquot A, Labaune JM, Baum TP, Putet G, Picaud JC. Rapid quantitative procalcitonin measurement to diagnose nosocomial infections in newborn infants. Arch Dis Child Fetal Neonatal Ed 2009;94:F345-8. 2. Flahault A, Cadilhac M, Thomas G. Sample size calculation should be performed for design accuracy in diagnostic test studies. J Clin Epidemiol 2005;58:859-62. 3. Buderer NM. Statistical methodology: I. Incorporating the prevalence of disease into the sample size calculation for sensitivity and specificity. Acad Emerg Med 1996;3:895-900. 4. Harper R, Reeves B. Reporting of precision of estimates for diagnostic accuracy: a review. BMJ 1999;318:1322-3. Competing interests: None |
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