A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis

Fischer, Joachim E.; Bachmann, Lucas M.; Jaeschke, Roman

doi:10.1007/s00134-003-1761-8

Cited by 891Sepsis Diagnosis and TreatmentMeta-analysis and systematic reviewsStatistical Methods in Epidemiology

A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis

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Fischer, Joachim E., Bachmann, Lucas M., Jaeschke, Roman·2003·Intensive Care Medicine

DOI 10.1007/s00134-003-1761-8

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Abstract

Background One of the most challenging practical and daily problems in intensive care medicine is the interpretation of the results from diagnostic tests. In neonatology and pediatric intensive care the early diagnosis of potentially life-threatening infections is a particularly important issue.Focus A plethora of tests have been suggested to improve diagnostic decision making in the clinical setting of infection which is a clinical example used in this article. Several criteria that are critical to evidence-based appraisal of published data are often not adhered to during the study or in reporting. To enhance the critical appraisal on articles on diagnostic tests we discuss various measures of test accuracy: sensitivity, specificity, receiver operating characteristic curves, positive and negative predictive values, likelihood ratios, pretest probability, posttest probability, and diagnostic odds ratio.Conclusions We suggest the following minimal requirements for reporting on the diagnostic accuracy of tests: a plot of the raw data, multilevel likelihood ratios, the area under the receiver operating characteristic curve, and the cutoff yielding the highest discriminative ability. For critical appraisal it is mandatory to report confidence intervals for each of these measures. Moreover, to allow comparison to the readers' patient population authors should provide data on study population characteristics, in particular on the spectrum of diseases and illness severity.

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The AUC values were in the acceptable range according to prior criteria.
“The AUC values ranged from .63 to .76 and were considered in acceptable range (Akobeng, 2007; Fischer et al., 2003).”
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Authors: Fischer, J. E., Bachmann, L. M., & Jaeschke, R.
Affiliations: University Children's Hospital Zurich (CH)
McMaster University (CA)
Corresponding author: Fischer, Joachim E.
ORCID: Fischer, Joachim E.
Bachmann, Lucas M.
Venue: Intensive Care Medicine
Publisher: Springer Science and Business Media LLC
Published: 2003-07-01
Volume: 29
Issue: 7
Pages: 1043-1051
ISSN: 0342-4642 (ISSN-L)
1432-1238
DOI: 10.1007/s00134-003-1761-8
OpenAlex: W1997033640
Cited by: 890
References: 28
Citations by year: 2026: 14 · 2025: 65 · 2024: 66 · 2023: 77 · 2022: 82 · 2021: 68 · 2020: 69 · 2019: 40 · 2018: 49 · 2017: 47 · 2016: 39 · 2015: 39 · 2014: 45 · 2013: 32 · 2012: 26
FWCI: 3.86
Type: journal article
Language: en
Open access: green
www.zora.uzh.ch
Licence: other-oa
www.springer.com/tdm (tdm)
Locations: Intensive Care Medicine (publishedVersion)
PubMed (publishedVersion)
Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
reroDoc Digital Library (submittedVersion)
Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
Zurich Open Repository and Archive (University of Zurich)
Topics: Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: diagnostic accuracy, sepsis, critical appraisal, sensitivity and specificity, likelihood ratios, predictive value, receiver operating characteristic, diagnostic odds ratio, reporting guidelines, infection diagnosis
MeSH terms: Bayes Theorem, Diagnostic Tests, Routine, Humans, ROC Curve, Sensitivity and Specificity, Switzerland, Confidence Intervals, Likelihood Functions, Odds Ratio, Sepsis

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A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis

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