A systematic review of the diagnostic accuracy of physical examination for the detection of cirrhosis

  • de Bruyn G
  • Graviss E
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Abstract

BACKGROUND:We conducted a review of the diagnostic accuracy of clinical examination for the diagnosis of cirrhosis. The objectives were: to identify studies assessing the accuracy of clinical examination in the detection of cirrhosis; to summarize the diagnostic accuracy of reported physical examination findings; and to define the effects of study characteristics on estimates of diagnostic accuracy.METHODS:Studies were identified through electronic literature search of MEDLINE (1966 to 2000), search of bibliographic references, and contact with authors. Studies that evaluated indicants from physical examination of patients with known or suspected liver disease undergoing liver biopsy were included. Qualitative data on study characteristics were extracted. Two-by-two tables of presence or absence of physical findings for patients with and without cirrhosis were created from study data. Data for physical findings reported in each study were combined using Summary Receiver Operating Characteristic (SROC) curves or random effects modeling, as appropriate.RESULTS:Twelve studies met inclusion criteria, including a total of 1895 patients, ranging in age from 3 to 90 years. Most studies were conducted in referral populations with elevated aminotransferase levels. Ten physical signs were reported in three or more studies and ten signs in only a single study. Signs for which there was more study data were associated with high specificity (range 75-98%), but low sensitivity (range 15-68%) for histologically-proven cirrhosis.CONCLUSIONS:Physical findings are generally of low sensitivity for the diagnosis of cirrhosis, and signs with higher specificity represent decompensated disease. Most studies have been undertaken in highly selected populations.

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de Bruyn, G., & Graviss, E. A. (2001). A systematic review of the diagnostic accuracy of physical examination for the detection of cirrhosis. BMC Medical Informatics and Decision Making, 1(1). https://doi.org/10.1186/1472-6947-1-6

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