Assessing likelihood ratio of clinical symptoms: handling vagueness
Received23 April 2003
revised18 July 2003
accepted11 August 2003
12 December 2017 (online)
Clinical symptoms including homeopathic symptoms are often vague. There is reluctance to assess clinical symptoms as diagnostic instruments because they are hard to define. Still, clinical symptoms appear effective in daily practice. Expert systems and neural networks handle vague data successfully.
Theoretical considerations predict the kind of problems we may expect. There is a difference between quantitative and qualitative vagueness. Vague data cause problems if we try to prove a hypothesis because of expectation bias. We assess likelihood ratio of homeopathic symptoms only to improve the method.
- 1 Stolper CF, Rutten ALB, Lugten RFG, Barthels RJWM. Improving homeopathic prescribing by applying epidemiological techniques: the role of likelihood ratio. Homeopathy 2002; 91: 230–238.
- 2 Rutten ALB, Stolper CF, Lugten RFG, Barthels RWJM. Is assessment of likelihood ratio of homeopathic symptoms possible? A pilot study. Homeopathy 2003; 92: 213–216.
- 3 Stanford Encyclopedia of Philosophy. Vagueness. http://plato.stanford.edu/entries/vagueness 2002.
- 4 Stanford Encyclopedia of Philosophy. Sorites paradox. http://plato.stanford.edu/entries/sorites-paradox 2002.
- 5 Graff D. An anti-epistemicist consequence of margin for error semantics for knowledge. Philos Phenomenol Res 2000; 64: 127–142.
- 6 Gavin WJ. William James and the Reinstatement of the Vague. Philadelphia: Temple University Press, 1992.
- 7 Bouter LM, Dongen MCJM van. 5.3.3 Confounding. Epidemiologisch onderzoek. Bohn Stafleu Van Loghum, 1995, pp 200–217.
- 8 Windolf J. What is the practical value of scoring systems? Zentralbl Chir 1999; 124: 687–691.
- 9 Fathi-Torbaghan M, Meyer D. MEDUSA: a fuzzy expert system for medical diagnosis of acute abdominal pain. Methods Inf Med 1994; 33: 522–529.
- 10 Innocent PR, John RI, Garibaldi JM. The fuzzy medical group in the centre for computational intelligence. Artif Intell Med 2001; 21: 163–170.
- 11 Weller SC, Mann NC. Assessing rater performance without a ‘gold standard’ using consensus theory. Med Decis Making 1997; 17: 71–79.
- 12 Simel DL, Samba PS, Matchar DB. Likelihood ratios for continuous test results—making the clinicians’ job easier or harder? J Clin Epidemiol 1993; 46: 85–93.
- 13 Jongh TOH de, Eekhof JAH, Berg H van den. Handelen in onzekerheid. Medisch Contact 2002; 57: 941–945.
- 14 Greenhalgh T. Intuition, evidence—uneasy bedfellows? Br J Gen Pract 2002; 52: 395–400.
- 15 Horton MD, Counter SF, Florence MG, Hart MJ. A prospective trial of computed tomography and ultrasonography for diagnosing appendicitis in the atypical patient. Am J Surg 2000; 179: 379–381.
- 16 Zielke A, Sitter H, Rampp T, Bohrer T, Rothmund M. Clinical decision-making, ultrasonography, and scores for evaluation of suspected acute appendicitis. World J Surg 2001; 25: 578–584.
- 17 Garcia-Aguayo FJ, Gil P. Sonography in acute appendicitis: diagnostic utility and influence upon management and outcome. Eur Radiol 2000; 10: 1886–1893.
- 18 Orr RK, Porter D, Hartman D. Ultrasonography to evaluate adults for appendicitis: decision making based on meta-analysis and probabilistic reasoning. Acad Emerg Med 1995; 2: 644–650.
- 19 Olive ST, Kiser WR. Diagnosis of appendicitis. J Am Board Fam Pract 1996; 9: 306–307.
- 20 Alvarado A. A practical score for the early diagnosis of acute appendicitis. Ann Emerg Med 1986; 15: 1048–1049.
- 21 Lisdonk EH van de, Bosch WHJM van den, Huygen FJA, Lagro-Janssen ALM. Ziekten in de huisartspraktijk. Bunge, 2002.
- 22 Flum DR, Morris A, Koepsell T, Dellinger EP. Has misdiagnosis of appendicitis decreased over time? A population-based analysis. JAMA 2001; 286: 1748–1753.