Diagnostic test (medical): Difference between revisions

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A '''diagnostic test''' is, as its name implies, a medical test or series of tests designed to examine a patient's ''signs'' or ''symptoms'' (what hurts, or what otherwise seems abnormal to the patient) in order to allow a medical practitioner to give a ''diagnosis'' (a conclusion) about what is wrong drawn an analysis of the patient's test results.  This is the first step in deciding how to treat the ailment or disease.
A '''diagnostic test''' is, as its name implies, a medical test or series of tests designed to examine a patient's ''signs'' or ''symptoms'' (what hurts, or what otherwise seems abnormal to the patient) in order to allow a medical practitioner to give a ''diagnosis'' (a conclusion) about what is wrong drawn an analysis of the patient's test results.  This is the first step in deciding how to treat the ailment or disease.


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===Recognize futility of testing when disease prevalence is extremely low===
===Recognize futility of testing when disease prevalence is extremely low===
<!-- under development -->
<!-- under development -->
Using [[Bayes Theorem]] may allow recognition that there are some settings where testing can be considred futile. Two conditions are necessary to establish futility:
Using [[Bayes Theorem]] may allow recognition that there are some settings where testing can be considered futile. Two conditions are necessary to establish futility:
# Being able to estimate the post-test probability of disease by having all the nessary information to do this: [[sensitivity  and specificity]] and prevalence of disease.
# Being able to estimate the post-test probability of disease by having all the necessary information to do this: [[sensitivity  and specificity]] and prevalence of disease.
# Evidence-based analysis of what post-test probability of disease is considered futile. For example, in the screening of [[HIV]], decision analysis calculates that screening should occur whenever prevalence is approximately 0.2%.<ref name="pmid17146064">{{cite journal |author=Paltiel AD, Walensky RP, Schackman BR, ''et al'' |title=Expanded HIV screening in the United States: effect on clinical outcomes, HIV transmission, and costs |journal=Ann. Intern. Med. |volume=145 |issue=11 |pages=797–806 |year=2006 |pmid=17146064 |doi=}}</ref> However, this type of analysis is not available for many diseases and, when is available, usually includes value judgments about futility and cost that may not be universally accepted judgments.
# Evidence-based analysis of what post-test probability of disease is considered futile. For example, in the screening of [[HIV]], decision analysis calculates that screening should occur whenever prevalence is approximately 0.2%.<ref name="pmid17146064">{{cite journal |author=Paltiel AD, Walensky RP, Schackman BR, ''et al'' |title=Expanded HIV screening in the United States: effect on clinical outcomes, HIV transmission, and costs |journal=Ann. Intern. Med. |volume=145 |issue=11 |pages=797–806 |year=2006 |pmid=17146064 |doi=}}</ref> However, this type of analysis is not available for many diseases and, when is available, usually includes value judgments about futility and cost that may not be universally accepted judgments.


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==References==
==References==
<references/>
{{reflist}}
 
[[Category:CZ Live]] [[Category:Health Sciences Workgroup]]

Revision as of 21:24, 19 February 2010

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A diagnostic test is, as its name implies, a medical test or series of tests designed to examine a patient's signs or symptoms (what hurts, or what otherwise seems abnormal to the patient) in order to allow a medical practitioner to give a diagnosis (a conclusion) about what is wrong drawn an analysis of the patient's test results. This is the first step in deciding how to treat the ailment or disease.

Some diagnostic tests may be similar to screening tests, however they differ from the latter in that screening tests are designed to discover abnormality before any symptoms are manifested; diagnostic tests take place after the patient has noticed symptoms of abnormality, illness or disease.

Interpreting diagnostic tests

See Sensitivity and specificity and Bayes Theorem

Non-specific benefit of tests

Medical tests can have value when results are abnormal by explaining to a patient the cause of their symptoms[1]. In addition, normal test results can have value by reassuring patients that serious illness is not present and even reduce the rates of subsequent symptoms [2].

If a normal test result is expected, understanding the meaning of a normal test in advance of learning the test results may reduce the rates of subsequent symptoms.[3][4]

Harms of tests

Labeling

Lack of adequate education about the meaning of test results (especially relevant to tests that may have incidental and unimportant findings) may cause an increase in symptoms[5] or anxiety[6]. This may be similar to the effects of labeling.[7]

Costs

The benefits must be weighed against the costs of resulting unnecessary follow-up and possibly even unnecessary treatment of incidental findings.[8]

Allowable costs of common tests according to the U.S. Centers for Medicare & Medicaid Services are available.[9]

Overdiagnosis

For more information, see: Overdiagnosis.


Other harms

Tests that seem harmless individually, may be harmful when repeated multiple times in a patient. For example in radiology, it is estimated that computed tomography may be contributing to cancer.[10]

About 7% of abnormal results are not communicated to patients. Physicians without a complete an electronic health record tend to provide worse follow-up on abnormal diagnostic tests.[11]

Strategies to reduce unnecessary diagnostic testing

A systematic review has found that multiple interventions are needed to best improve test ordering.[12]

Improve availability of prior results

Sometimes testing is redundant.[13] Having the results of prior tests available may reduce the need for repeating tests.[14] A randomized controlled trial has shown reduction i ordering of redundant tests.[15]

Delay testing

Randomized controlled trials show benefit of immediate versus delayed testing in patients without possible emergent conditions.[5][8] The benefit may be in part due to successful empirical treatment.

Establish an alternative diagnoses

Studies show that the chance of thromboembolism is less in patients who have have alternative explanations for their symptoms.[16][17]

Patients with chronic abdominal symptoms are less likely to have underlying organic disease if they meet criteria for irritable bowel.[18][19][20]

Among patients referred for endoscopy, psychiatric diagnoses are associated with normal endoscopies.[21]

Patients with new headaches are less likely to have significant underlying pathology if their headaches meet criteria for being a migraine headache according to a systematic review by the Rational Clinical Examination.[22] The systematic review found two relevant studies:[22]

  • Among 69 patients over 40 years old with new migraines, no patients had definite significant intracranial pathology (4 patients had evidence of prior infarctions).[23]
  • Among 100 adults with new, non-specific headaches, approximately 40% had underlying pathology.[24]

Recognize futility of testing when disease prevalence is extremely low

Using Bayes Theorem may allow recognition that there are some settings where testing can be considered futile. Two conditions are necessary to establish futility:

  1. Being able to estimate the post-test probability of disease by having all the necessary information to do this: sensitivity and specificity and prevalence of disease.
  2. Evidence-based analysis of what post-test probability of disease is considered futile. For example, in the screening of HIV, decision analysis calculates that screening should occur whenever prevalence is approximately 0.2%.[25] However, this type of analysis is not available for many diseases and, when is available, usually includes value judgments about futility and cost that may not be universally accepted judgments.

Examples where thresholds are established or implied to justify testing or treatment include:

  • HIV screening - the threshold is very low.[25] Screening is recommended even if the prevalence is as low as 0.2%.[25]
  • Influenza treatment - the threshold is higher as the stakes are lower. For elderly patients, treatment should be initiated if probability of disease is 13% or more.[26] while for younger patients the threshold is 30%.[27][26]

In the absence of specific analysis, another approach to determining the appropriate threshold is to use precedent. For example, in potentially lethal diseases such as pulmonary embolism[28], acute coronary syndrome[29], and pneumonia[30][31], in the best of health care settings 2-4% of patients have their diagnosis missed.Therefore, the precedent would be that whenever a serious disease is estimated to have more than a 2%-4% prevalence, the disease should be sought.

A randomized controlled trial showed a small reduction in test ordering when a computer displayed very low probabilities that a test would be abnormal.[32]

Response to empiric treatment

Although this strategy seems sensible, there are reports of misleading responses by serious diseases to empiric treatment for chest pain[33][34] and headache[35][36]

These responses may be due to non-specific actions of the drugs used, or may be due to placebo effect.

Research studies of the accuracy of diagnostic tests

Poorly designed studies may overestimate the accuracy of a diagnostic test.[37]

Publication bias

Publication bias may inflate the reported accuracies of diagnostic tests.[38] Publication bias may be more of a problem in diagnostic test research than in randomized controlled trials because studies of diagnostic tests can be secondary analyses of databases and do not have to be registered prior to publication.[39]

For the detection of publication bias in meta-analysis of diagnostic tests, the effective sample size funnel plot and associated regression test of asymmetry may be used.[40]The

Standards for the conduct and reporting of studies of diagnostic tests

Standards are available (http://www.stard-statement.org/).[41][42][43]

The STARD statement is encouraged by 38% or clinical medical journals that published diagnostic tests.[44] STARD was more often encouraged by general and internal medicine scientific journals (46%) than in specialty scientific journals(35%).

References

  1. Ward B, Wu W, Richter J, Hackshaw B, Castell D (1987). "Long-term follow-up of symptomatic status of patients with noncardiac chest pain: is diagnosis of esophageal etiology helpful?". Am J Gastroenterol 82 (3): 215-8. PMID 3826028.
  2. Sox H, Margulies I, Sox C (1981). "Psychologically mediated effects of diagnostic tests". Ann Intern Med 95 (6): 680-5. PMID 7305144.
  3. Petrie K, Müller J, Schirmbeck F, Donkin L, Broadbent E, Ellis C, Gamble G, Rief W (2007). "Effect of providing information about normal test results on patients' reassurance: randomised controlled trial". BMJ 334: 352. PMID 17259186.
  4. Thomas Mordekhai Laurence (2004). Extreme Clinic -- An Outpatient Doctor's Guide to the Perfect 7 Minute Visit. Philadelphia: Hanley & Belfus. ISBN 1-56053-603-9. 
  5. 5.0 5.1 Kendrick D, Fielding K, Bentley E, Kerslake R, Miller P, Pringle M (2001). "Radiography of the lumbar spine in primary care patients with low back pain: randomised controlled trial". BMJ 322 (7283): 400-5. PMID 11179160.
  6. Hoefman E, Boer KR, van Weert HC, Reitsma JB, Koster RW, Bindels PJ (2007). "Continuous event recorders did not affect anxiety or quality of life in patients with palpitations". Journal of clinical epidemiology 60 (10): 1060–6. DOI:10.1016/j.jclinepi.2007.01.014. PMID 17884602. Research Blogging.
  7. Haynes RB, Sackett DL, Taylor DW, Gibson ES, Johnson AL (1978). "Increased absenteeism from work after detection and labeling of hypertensive patients". N. Engl. J. Med. 299 (14): 741–4. PMID 692548[e]
  8. 8.0 8.1 Jarvik J, Hollingworth W, Martin B, Emerson S, Gray D, Overman S, Robinson D, Staiger T, Wessbecher F, Sullivan S, Kreuter W, Deyo R (2003). "Rapid magnetic resonance imaging vs radiographs for patients with low back pain: a randomized controlled trial". JAMA 289 (21): 2810-8. PMID 12783911.
  9. Anonymous. Fee Schedule Clinical Laboratory Fee Schedule. Centers for Medicare & Medicaid Services.
  10. Brenner DJ, Hall EJ (2007). "Computed tomography--an increasing source of radiation exposure". N. Engl. J. Med. 357 (22): 2277–84. DOI:10.1056/NEJMra072149. PMID 18046031. Research Blogging.
  11. Casalino, Lawrence P.; Daniel Dunham, Marshall H. Chin, Rebecca Bielang, Emily O. Kistner, Theodore G. Karrison, Michael K. Ong, Urmimala Sarkar, Margaret A. McLaughlin, David O. Meltzer (2009-06-22). "Frequency of Failure to Inform Patients of Clinically Significant Outpatient Test Results". Arch Intern Med 169 (12): 1123-1129. DOI:10.1001/archinternmed.2009.130. Retrieved on 2009-06-23. Research Blogging.
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  13. Bates DW, Boyle DL, Rittenberg E, et al (1998). "What proportion of common diagnostic tests appear redundant?". Am. J. Med. 104 (4): 361–8. PMID 9576410[e]
  14. Tierney WM, McDonald CJ, Martin DK, Rogers MP (1987). "Computerized display of past test results. Effect on outpatient testing". Ann. Intern. Med. 107 (4): 569–74. PMID 3631792[e]
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  16. Wells P, Anderson D, Rodger M, Ginsberg J, Kearon C, Gent M, Turpie A, Bormanis J, Weitz J, Chamberlain M, Bowie D, Barnes D, Hirsh J (2000). "Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer.". Thromb Haemost 83 (3): 416-20. PMID 10744147.
  17. Wells PS, Anderson DR, Rodger M, Stiell I, Dreyer JF, Barnes D, Forgie M, Kovacs G, Ward J, Kovacs MJ (2001). "Excluding pulmonary embolism at the bedside without diagnostic imaging: management of patients with suspected pulmonary embolism presenting to the emergency department by using a simple clinical model and d-dimer". Ann Intern Med 135 (2): 98-107. PMID 11453709.
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  22. 22.0 22.1 Detsky ME, McDonald DR, Baerlocher MO, Tomlinson GA, McCrory DC, Booth CM (2006). "Does this patient with headache have a migraine or need neuroimaging?". JAMA 296 (10): 1274–83. DOI:10.1001/jama.296.10.1274. PMID 16968852. Research Blogging.
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  25. 25.0 25.1 25.2 Paltiel AD, Walensky RP, Schackman BR, et al (2006). "Expanded HIV screening in the United States: effect on clinical outcomes, HIV transmission, and costs". Ann. Intern. Med. 145 (11): 797–806. PMID 17146064[e] Cite error: Invalid <ref> tag; name "pmid17146064" defined multiple times with different content
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