Diagnostic test (medical): Difference between revisions

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Examples where thresholds are established or implied to justify testing or treatment include:
Examples where thresholds are established or implied to justify testing or treatment include:
* [[HIV]] screening - the threshold is very low.<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= |issn=}}</ref> Screening is recommended even if the prevalence is as low as 0.2%.<ref name="pmid17146064"/>
* [[HIV]] screening - the threshold is very low.<ref name="pmid17146064" /> Screening is recommended even if the prevalence is as low as 0.2%.<ref name="pmid17146064"/>
* [[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.<ref name="pimd12965940">{{cite journal | author = Rothberg M, Bellantonio S, Rose D | title = Management of influenza in adults older than 65 years of age: cost-effectiveness of rapid testing and antiviral therapy. | journal = Ann Intern Med | volume = 139 | issue = 5 Pt 1 | pages = 321-9 | year = 2003 | url = http://www.annals.org/cgi/content/abstract/139/5_Part_1/321 | id = PMID 12965940}}</ref> while for younger patients the threshold is 30%.<ref name="pmid12361816">{{cite journal | author = Smith K, Roberts M | title = Cost-effectiveness of newer treatment strategies for influenza. | journal = Am J Med | volume = 113 | issue = 4 | pages = 300-7 | year = 2002 | doi = 10.1016/S0002-9343(02)01222-6 | id = PMID 12361816}}</ref><ref name="pimd12965940">{{cite journal | author = Rothberg M, Bellantonio S, Rose D | title = Management of influenza in adults older than 65 years of age: cost-effectiveness of rapid testing and antiviral therapy. | journal = Ann Intern Med | volume = 139 | issue = 5 Pt 1 | pages = 321-9 | year = 2003 | url = http://www.annals.org/cgi/content/abstract/139/5_Part_1/321 | id = PMID 12965940}}</ref>
* [[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.<ref name="pimd12965940">{{cite journal | author = Rothberg M, Bellantonio S, Rose D | title = Management of influenza in adults older than 65 years of age: cost-effectiveness of rapid testing and antiviral therapy. | journal = Ann Intern Med | volume = 139 | issue = 5 Pt 1 | pages = 321-9 | year = 2003 | url = http://www.annals.org/cgi/content/abstract/139/5_Part_1/321 | id = PMID 12965940}}</ref> while for younger patients the threshold is 30%.<ref name="pmid12361816">{{cite journal | author = Smith K, Roberts M | title = Cost-effectiveness of newer treatment strategies for influenza. | journal = Am J Med | volume = 113 | issue = 4 | pages = 300-7 | year = 2002 | doi = 10.1016/S0002-9343(02)01222-6 | id = PMID 12361816}}</ref><ref name="pimd12965940">{{cite journal | author = Rothberg M, Bellantonio S, Rose D | title = Management of influenza in adults older than 65 years of age: cost-effectiveness of rapid testing and antiviral therapy. | journal = Ann Intern Med | volume = 139 | issue = 5 Pt 1 | pages = 321-9 | year = 2003 | url = http://www.annals.org/cgi/content/abstract/139/5_Part_1/321 | id = PMID 12965940}}</ref>


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===Incorporation bias or reference standard review bias===
===Incorporation bias or reference standard review bias===
Incorporation bias or reference standard review bias occurs when interpretation of the final diagnosis is affected by knowledge of the diagnostic test.<ref name="pmid692598">{{cite journal| author=Ransohoff DF, Feinstein AR| title=Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. | journal=N Engl J Med | year= 1978 | volume= 299 | issue= 17 | pages= 926-30 | pmid=692598  
Incorporation bias or reference standard review bias occurs when interpretation of the final diagnosis is affected by knowledge of the diagnostic test.<ref name="pmid692598">{{cite journal| author=Ransohoff DF, Feinstein AR| title=Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. | journal=N Engl J Med | year= 1978 | volume= 299 | issue= 17 | pages= 926-30 | pmid=692598  
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=692598 }} </ref><ref name="pmid16519814">{{cite journal| author=Whiting PF, Weswood ME, Rutjes AW, Reitsma JB, Bossuyt PN, Kleijnen J| title=Evaluation of QUADAS, a tool for the quality assessment of diagnostic accuracy studies. | journal=BMC Med Res Methodol | year= 2006 | volume= 6 | issue=  | pages= 9 | pmid=16519814
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=692598 }} </ref><ref name="pmid16519814" />
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=16519814 | doi=10.1186/1471-2288-6-9 | pmc=PMC1421422 }} </ref>


===Spectrum bias===
===Spectrum bias===
Spectrum bias may occur when a study includes patients with know disease and separately identified healthy subjects without subjects with intermediate probability of disease.<ref name="pmid692598">{{cite journal| author=Ransohoff DF, Feinstein AR| title=Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. | journal=N Engl J Med | year= 1978 | volume= 299 | issue= 17 | pages= 926-30 | pmid=692598  
Spectrum bias may occur when a study includes patients with know disease and separately identified healthy subjects without subjects with intermediate probability of disease.<ref name="pmid692598">{{cite journal| author=Ransohoff DF, Feinstein AR| title=Problems of spectrum and bias in evaluating the efficacy of diagnostic tests. | journal=N Engl J Med | year= 1978 | volume= 299 | issue= 17 | pages= 926-30 | pmid=692598  
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=692598 }} </ref><ref name="pmid12353947">{{cite journal| author=Mulherin SA, Miller WC| title=Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation. | journal=Ann Intern Med | year= 2002 | volume= 137 | issue= 7 | pages= 598-602 | pmid=12353947  
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=692598 }} </ref><ref name="pmid12353947">{{cite journal| author=Mulherin SA, Miller WC| title=Spectrum bias or spectrum effect? Subgroup variation in diagnostic test evaluation. | journal=Ann Intern Med | year= 2002 | volume= 137 | issue= 7 | pages= 598-602 | pmid=12353947  
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=12353947 }} </ref> When two distinct groups are compared in this way, the study in effect becomes a [[case control study]] which has been shown to overestimate diagnostic test accuracy.<ref name="pmid10493205">{{cite journal| author=Lijmer JG, Mol BW, Heisterkamp S, Bonsel GJ, Prins MH, van der Meulen JH et al.| title=Empirical evidence of design-related bias in studies of diagnostic tests. | journal=JAMA | year= 1999 | volume= 282 | issue= 11 | pages= 1061-6 | pmid=10493205
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=12353947 }} </ref> When two distinct groups are compared in this way, the study in effect becomes a [[case control study]] which has been shown to overestimate diagnostic test accuracy.<ref name="pmid10493205" />
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=10493205 }} </ref>


Multivariable adjustments may counteract spectrum bias.<ref name="pmid18620840">{{cite journal| author=Bachmann LM, ter Riet G, Weber WE, Kessels AG| title=Multivariable adjustments counteract spectrum and test review bias in accuracy studies. | journal=J Clin Epidemiol | year= 2009 | volume= 62 | issue= 4 | pages= 357-361.e2 | pmid=18620840  
Multivariable adjustments may counteract spectrum bias.<ref name="pmid18620840">{{cite journal| author=Bachmann LM, ter Riet G, Weber WE, Kessels AG| title=Multivariable adjustments counteract spectrum and test review bias in accuracy studies. | journal=J Clin Epidemiol | year= 2009 | volume= 62 | issue= 4 | pages= 357-361.e2 | pmid=18620840  
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The STARD statement is encouraged by 38% or clinical medical journals that published diagnostic tests.<ref name="pmid17954503">{{cite journal |author=Smidt N, Overbeke J, de Vet H, Bossuyt P |title=Endorsement of the STARD Statement by biomedical journals: survey of instructions for authors |journal=Clin. Chem. |volume=53 |issue=11 |pages=1983–5 |year=2007 |month=November |pmid=17954503 |doi=10.1373/clinchem.2007.090167 |url=http://www.clinchem.org/cgi/pmidlookup?view=long&pmid=17954503 |issn=}}</ref> STARD was more often encouraged by general and internal medicine [[scientific journal]]s (46%) than in specialty [[scientific journal]]s(35%).
The STARD statement is encouraged by 38% or clinical medical journals that published diagnostic tests.<ref name="pmid17954503">{{cite journal |author=Smidt N, Overbeke J, de Vet H, Bossuyt P |title=Endorsement of the STARD Statement by biomedical journals: survey of instructions for authors |journal=Clin. Chem. |volume=53 |issue=11 |pages=1983–5 |year=2007 |month=November |pmid=17954503 |doi=10.1373/clinchem.2007.090167 |url=http://www.clinchem.org/cgi/pmidlookup?view=long&pmid=17954503 |issn=}}</ref> STARD was more often encouraged by general and internal medicine [[scientific journal]]s (46%) than in specialty [[scientific journal]]s(35%).


The Quality Assessment of Diagnostic  Accuracy Assessment (QUADAS) tool can help assess quality of studies of diagnostic tests.<ref  name="pmid16519814">{{cite journal|  author=Whiting PF, Weswood ME, Rutjes AW, Reitsma JB, Bossuyt PN,  Kleijnen J| title=Evaluation of QUADAS, a tool for the quality  assessment of diagnostic  accuracy studies. | journal=BMC Med Res Methodol | year= 2006 | volume= 6  | issue=  | pages= 9 | pmid=16519814
The Quality Assessment of Diagnostic  Accuracy Assessment (QUADAS) tool can help assess quality of studies of diagnostic tests.<ref  name="pmid16519814" /> The QUADAS-2 revision is available.<ref>{{Cite journal
| url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=clinical.uthscsa.edu/cite&retmode=ref&cmd=prlinks&id=16519814  | doi=10.1186/1471-2288-6-9 | pmc=PMC1421422 }} </ref><ref>Diagnostic Test Accuracy Working Group (2009) [Chapter 9: Assessing methodological quality http://srdta.cochrane.org/sites/srdta.cochrane.org/files/uploads/ch09_Oct09.pdf] in [http://srdta.cochrane.org/handbook-dta-reviews Handbook for DTA Reviews]. Cochrane Collaboration</ref> The QUADAS-2 revision is available.<ref>{{Cite journal
| doi = 10.1059/0003-4819-155-8-201110180-00009
| doi = 10.1059/0003-4819-155-8-201110180-00009
| volume = 155
| volume = 155

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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 also Bayes Theorem, sensitivity and specificity, and likelihood ratio.

Interpreting and comparing studies of diagnostic tests is difficult. Although standards exists for meta-analysis of randomized controlled trials and cohort studies[1], no guidelines exist for studies of diagnostic test accuracy. In addition, the Cochrane Collaboration has not finished their handbook of meta-analyses of diagnostic test accuracy[2] although the Cochrane Diagnostic Test Accuracy Working Group has published recommendations.[3].

Methods to compare diagnostic tests
Method Advantages Disadvantages
Simple accuracy Easy to understand Varies with prevalence of disease
Gain in Certainty[4]
(Sensitivity plus specificity)		 Easy to understand
Stable with prevalence of disease
Youden's J index[5]
(Sensitivity plus specificity minus 1)		 Easy to understand
Stable with prevalence of disease
Area under the receiver operating characteristic curve (AROC)[6] and variations[3] Stable with prevalence of disease
Can interpret multi-level and continuous outcome tests		 Hard to understand
Diagnostic odds ratio (DOR)[7] Stable with prevalence of disease
Can be included in multivariable analyses		 Hard to understand
Underestimates heterogeneity[8]
Net reclassification index[9]
Change in sensitivity plus change in specificity		 Stable with prevalence of disease
Can interpret multi-level tests		 Hard to understand

Non-specific benefit of tests

Medical tests can have value when results are abnormal by explaining to a patient the cause of their symptoms[10]. 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 [11].

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.[12][13]

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[14] or anxiety[15]. This may be similar to the effects of labeling.[16]

Costs

The benefits must be weighed against the costs of resulting unnecessary follow-up and possibly even unnecessary treatment of incidental findings.[17]

Allowable costs of common tests according to the U.S. Centers for Medicare & Medicaid Services are available.[18]

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.[19]

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.[20]

Strategies to reduce unnecessary diagnostic testing

A systematic review has found that multiple interventions are needed to best improve test ordering.[21]

Improve availability of prior results

Sometimes testing is redundant.[22] Having the results of prior tests available may reduce the need for repeating tests.[23] A randomized controlled trial has shown reduction i ordering of redundant tests.[24]

Delay testing

Randomized controlled trials show benefit of immediate versus delayed testing in patients without possible emergent conditions.[14][17] 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.[25][26]

Patients with chronic abdominal symptoms are less likely to have underlying organic disease if they meet criteria for irritable bowel.[27][28][29]

Among patients referred for endoscopy, psychiatric diagnoses are associated with normal endoscopies.[30]

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.[31] The systematic review found two relevant studies:[31]

  • Among 69 patients over 40 years old with new migraines, no patients had definite significant intracranial pathology (4 patients had evidence of prior infarctions).[32]
  • Among 100 adults with new, non-specific headaches, approximately 40% had underlying pathology.[33]

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%.[34] 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.[34] Screening is recommended even if the prevalence is as low as 0.2%.[34]
  • 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.[35] while for younger patients the threshold is 30%.[36][35]

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[37], acute coronary syndrome[38], and pneumonia[39][40], 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.[41]

Response to empiric treatment

Although this strategy seems sensible, there are reports of misleading responses by serious diseases to empiric treatment for chest pain[42][43] and headache[44][45]

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.[46]

The Quality Assessment of Diagnostic Accuracy Assessment (QUADAS) is an 14 item scale for assessing the quality of a diagnostic test that is used by the Cochrane Collaboration.[47][48]

Context bias

Diagnostic tests that are interpreted subjectively may be influence by the prevalence of disease.[49]

Incorporation bias or reference standard review bias

Incorporation bias or reference standard review bias occurs when interpretation of the final diagnosis is affected by knowledge of the diagnostic test.[50][47]

Spectrum bias

Spectrum bias may occur when a study includes patients with know disease and separately identified healthy subjects without subjects with intermediate probability of disease.[50][51] When two distinct groups are compared in this way, the study in effect becomes a case control study which has been shown to overestimate diagnostic test accuracy.[46]

Multivariable adjustments may counteract spectrum bias.[52]

Test review bias

Test review bias occurs when interpretation of a subjective test is done with additional knowledge of the patient. Interpreters of subjective tests should be blinded to other information about the patient. Multivariable adjustments may counteract test review bias.[52]

Verification bias

Verification bias can inflate the accuracy of test results in a study.[53]

Publication bias

Publication bias may inflate the reported accuracies of diagnostic tests.[54] 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.[55]

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.[56]The

Standards for the conduct and reporting of studies of diagnostic tests

Standards are available (http://www.stard-statement.org/).[57][58][59]

The STARD statement is encouraged by 38% or clinical medical journals that published diagnostic tests.[60] STARD was more often encouraged by general and internal medicine scientific journals (46%) than in specialty scientific journals(35%).

The Quality Assessment of Diagnostic Accuracy Assessment (QUADAS) tool can help assess quality of studies of diagnostic tests.[47] The QUADAS-2 revision is available.[61]

Recommendations are available for reading studies of diagnostic test accuracy.[62][63]

References

  1. ↑ http://www.equator-network.org/resource-centre/library-of-health-research-reporting/reporting-guidelines/systematic-reviews-and-meta-analysis/
  2. ↑ Diagnostic Test Accuracy Working Group. Handbook for DTA Reviews. The Cochrane Collaboration
  3. ↑ 3.0 3.1 Leeflang MM, Deeks JJ, Gatsonis C, Bossuyt PM, Cochrane Diagnostic Test Accuracy Working Group (2008). "Systematic reviews of diagnostic test accuracy.". Ann Intern Med 149 (12): 889-97. PMID 19075208.
  4. ↑ Connell FA, Koepsell TD (May 1985). "Measures of gain in certainty from a diagnostic test". Am. J. Epidemiol. 121 (5): 744–53. PMID 4014166. [e]
  5. ↑ Youden WJ (January 1950). "Index for rating diagnostic tests". Cancer 3 (1): 32–5. PMID 15405679. [e]
  6. ↑ Hanley JA, McNeil BJ (1982). "The meaning and use of the area under a receiver operating characteristic (ROC) curve.". Radiology 143 (1): 29-36. PMID 7063747.
  7. ↑ Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM (2003). "The diagnostic odds ratio: a single indicator of test performance.". J Clin Epidemiol 56 (11): 1129-35. PMID 14615004.
  8. ↑ Cornell J, Mulrow CD, Localio AR (2008). "Diagnostic test accuracy and clinical decision making.". Ann Intern Med 149 (12): 904-6. PMID 19075211.
  9. ↑ Pencina MJ, D'Agostino RB, D'Agostino RB, Vasan RS (2008). "Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.". Stat Med 27 (2): 157-72; discussion 207-12. DOI:10.1002/sim.2929. PMID 17569110. Research Blogging.
  10. ↑ 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.
  11. ↑ Sox H, Margulies I, Sox C (1981). "Psychologically mediated effects of diagnostic tests". Ann Intern Med 95 (6): 680-5. PMID 7305144.
  12. ↑ 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.
  13. ↑ 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. 
  14. ↑ 14.0 14.1 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.
  15. ↑ 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.
  16. ↑ 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]
  17. ↑ 17.0 17.1 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.
  18. ↑ Anonymous. Fee Schedule Clinical Laboratory Fee Schedule. Centers for Medicare & Medicaid Services.
  19. ↑ 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.
  20. ↑ 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.
  21. ↑ Solomon DH, Hashimoto H, Daltroy L, Liang MH (1998). "Techniques to improve physicians' use of diagnostic tests: a new conceptual framework". JAMA 280 (23): 2020–7. PMID 9863854. [e]
  22. ↑ 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]
  23. ↑ 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]
  24. ↑ Bates DW, Kuperman GJ, Rittenberg E, et al (1999). "A randomized trial of a computer-based intervention to reduce utilization of redundant laboratory tests". Am. J. Med. 106 (2): 144–50. PMID 10230742. [e]
  25. ↑ 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.
  26. ↑ 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.
  27. ↑ Kruis W, Thieme C, Weinzierl M, Schüssler P, Holl J, Paulus W (1984). "A diagnostic score for the irritable bowel syndrome. Its value in the exclusion of organic disease.". Gastroenterology 87 (1): 1-7. PMID 6724251.
  28. ↑ Bellentani S, Baldoni P, Petrella S, Tata C, Armocida C, Marchegiano P, Saccoccio G, Manenti F (1990). "A simple score for the identification of patients at high risk of organic diseases of the colon in the family doctor consulting room. The Local IBS Study Group.". Fam Pract 7 (4): 307-12. PMID 2289644.
  29. ↑ Frigerio G, Beretta A, Orsenigo G, Tadeo G, Imperiali G, Minoli G (1992). "Irritable bowel syndrome. Still far from a positive diagnosis.". Dig Dis Sci 37 (2): 164-7. PMID 1735330.
  30. ↑ O'Malley PG, Wong PW, Kroenke K, Roy MJ, Wong RK (1998). "The value of screening for psychiatric disorders prior to upper endoscopy". Journal of psychosomatic research 44 (2): 279–87. PMID 9532557. [e]
  31. ↑ 31.0 31.1 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.
  32. ↑ Cull RE (1995). "Investigation of late-onset migraine". Scott Med J 40 (2): 50–2. PMID 7618069. [e]
  33. ↑ Duarte J, Sempere AP, Delgado JA, Naranjo G, Sevillano MD, Clavería LE (1996). "Headache of recent onset in adults: a prospective population-based study". Acta Neurol. Scand. 94 (1): 67–70. PMID 8874597. [e]
  34. ↑ 34.0 34.1 34.2 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]
  35. ↑ 35.0 35.1 Rothberg M, Bellantonio S, Rose D (2003). "Management of influenza in adults older than 65 years of age: cost-effectiveness of rapid testing and antiviral therapy.". Ann Intern Med 139 (5 Pt 1): 321-9. PMID 12965940.
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  48. ↑ Diagnostic Test Accuracy Working Group (2009) [Chapter 9: Assessing methodological quality http://srdta.cochrane.org/sites/srdta.cochrane.org/files/uploads/ch09_Oct09.pdf] in Handbook for DTA Reviews. Cochrane Collaboration
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