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Record W2125964936 · doi:10.1155/2009/879274

‘Virtual Colonoscopy’ – What’s in a Name?

2009· editorial· en· W2125964936 on OpenAlexaffvenue
Guido Van Rosendaal

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2009
Typeeditorial
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColonoscopyVirtual colonoscopyMedicineComputer scienceInternal medicineColorectal cancerCancer

Abstract

fetched live from OpenAlex

After hearing about the risks associated with colonoscopy, a patient asks “What about virtual colonoscopy?” The message she received is clear – there is a test that is essentially equivalent to a real colonoscopy but without the risks or discomfort that are associated with the actual procedure. Computed tomography (CT) colonography or spiral CT scanning of the colon is presented to the public with a label that includes an embedded message – ‘this is a good test that rivals colonoscopy.’ Mislabelling has been fairly common in medicine, often the result of a misunderstanding of the underlying cause of a symptom or disease. Dyspepsia (ie, indigestion) is not really due to a defect of the digestive process, and we have come to understand that ‘heart burn’ has nothing to do with the heart. An elderly physician once told me that in the early days of his practice people were said to die of ‘acute indigestion’, a term eventually replaced with ‘myocardial infarction’ or ‘heart attack’ when we came to understand what was actually happening to these patients. However, ‘virtual colonoscopy’ is not a label that comes from a misunderstanding of its nature or value. It is a label directed at the consumer and actually seeks to place the procedure in a position of some equivalency with colonoscopy. Is this OK? Is it acceptable to embed a marketing message in the name of an option for a consumer who needs to make an important choice among a range of screening options? Such labelling is, after all, quite effective at influencing consumers. Are the strategies of consumer advertising germane to or even ethical in the world of medicine? Is it not objectivity and accuracy that we must provide to patients? Language evolves and becomes normative from general use. It becomes difficult to expunge a term from our common discourse once we have reached a certain level of familiarity and comfort with it. Those who have sought to change the language of ‘stroke’ to ‘brain attack’ have found this to be a difficult proposition. It is still relatively early in our experience with CT imaging of the colon, so we still have an opportunity to reconsider the use of the term ‘virtual colonoscopy’. In the interest of objectivity, I suggest that we should call a thing what it is and not label it in a way that suggests something about its relative efficacy or risk. When I talk to patients about their use of analgesic combinations containing acetaminophen and codeine, I discuss their use of codeine; I do not use the name of the commercial preparation they are taking (why would one name a combination of drugs after the ingredient that provides only minor efficacy in the formulation and tag the narcotic component – the one with addictive potential – as a number?). I suggest that we cease and desist in our use of the term ‘virtual colonoscopy’ and call the procedure what it is. It is CT colonography, or spiral or helical CT scanning of the colon. This is the language that I use when discussing this procedure with patients. As physicians, we should strive to make the language of medicine as objective, accurate and meaningful as we can, understanding that ultimately we may have little impact on the lingua franca.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.012
Scholarly communication0.0090.016
Open science0.0010.004
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0230.015

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.250
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2009
Admission routes2
Has abstractyes

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