Nomogram for Bayes's Theorem
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Considering an estimated prevalence of AMI of 1% among acute abdominal pain patients, the probability of AMI would be approximately 0.01% or 10% for a patient with no or two factors, respectively.
“Considering an estimated prevalence of AMI of 1% among acute abdominal pain patients [2, 3], the probability of AMI would be approximately 0.01% or 10% for a patient with no or two factors, respectively [21].”
From Improving clinical suspicion of acute mesenteric ischemia among patients with acute abdomen: A cross-sectional study from an intestinal stroke center (2023) · cites this paper as [21]
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- Authors
- Fagan, T. J.
- Corresponding author
- T. J. Fagan
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1975-07-31
- Volume
- 293
- Issue
- 5
- Pages
- 257-257
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W191064394
- Cited by
- 1,017
- References
- 0
- Citations by year
- 2026: 38 · 2025: 36 · 2024: 34 · 2023: 46 · 2022: 49 · 2021: 45 · 2020: 50 · 2019: 46 · 2018: 42 · 2017: 39 · 2016: 38 · 2015: 37 · 2014: 27 · 2013: 35 · 2012: 36
- FWCI
- 2.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- Bayes' theorem, nomogram, conditional probability, diagnostic testing, likelihood ratios, pretest probability, post-test probability
- MeSH terms
- Bayes Theorem, Diagnosis, Humans, Hypertension, Renal, Probability
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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