The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain
Abstract
To determine whether data available to physicians in the emergency room can accurately identify which patients with acute chest pain are having myocardial infarctions, we analyzed 482 patients at one hospital. Using recursive partitioning analysis, we constructed a decision protocol in the format of a simple flow chart to identify infarction on the basis of nine clinical factors. In prospective testing on 468 other patients at a second hospital, the protocol performed as well as the physicians. Moreover, an integration of the protocol with the physicians' judgments resulted in a classification system that preserved sensitivity for detecting infarctions, significantly improved the specificity (from 67 per cent to 77 per cent, P less than 0.01) and positive predictive value (from 34 per cent to 42 per cent, P = 0.016) of admission to an intensive-care area. The protocol identified a subgroup of 107 patients among whom only 5 per cent had infarctions and for whom admission to non-intensive-care areas might be appropriate. This decision protocol warrants further wide-scale prospective testing but is not ready for routine clinical use.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bootstrap methods: another look at the jackknife
Efron, B. (1979) · The Annals of Statistics · doi:10.1214/aos/1176344552 · Cited by 17,602
(2005) · Integrative Oncology · doi:10.1201/9780203088319-19 · Cited by 1,579
The development of mature gait.
Sutherland, D. H., Olshen, R., Cooper, L., & Woo, S. L. (1980) · The Journal of Bone & Joint Surgery · doi:10.2106/00004623-198062030-00004 · Cited by 840
Self-citationAn Analysis of Variance for Categorical Data
Light, R. J., & Margolin, B. H. (1971) · Journal of the American Statistical Association · doi:10.1080/01621459.1971.10482297 · Cited by 329
ACUTE PHASE OF MYOCARDIAL INFARCTION
Adgey, A. A. J., Geddes, J. S., Webb, S. W., Allen, J. D., James, R. G. G., Zaidi, S. A., & Pantridge, J. F. (1971) · The Lancet · doi:10.1016/s0140-6736(71)90434-x · Cited by 232
Myocardial infarction: a comparison between home and hospital care for patients.
Mather, H. G., Morgan, D. C., Pearson, N. G., Read, K. L., Shaw, D. B., Steed, G. R., Thorne, M. G., Lawrence, C. J., & Riley, I. S. (1976) · BMJ · doi:10.1136/bmj.1.6015.925 · Cited by 203
Hill, J. D., Hampton, J. R., & Mitchell, J. R. A. (1978) · The Lancet · doi:10.1016/s0140-6736(78)90190-3 · Cited by 186
Prodromata of myocardial infarction and sudden death.
Alonzo, A. A., Simon, A. B., & Feinleib, M. (1975) · Circulation · doi:10.1161/01.cir.52.6.1056 · Cited by 132
Asymptotically Efficient Solutions to the Classification Problem
Gordon, L., & Olshen, R. A. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344197 · Cited by 114
Self-citationA Practical Device for the Application of a Diagnostic or Prognostic Function
Lubsen, J. C., Pool, J., & van der Does, E. (1978) · Methods of Information in Medicine · doi:10.1055/s-0038-1636613 · Cited by 68
Cited by
Braunwald, E., Antman, E. M., Beasley, J. W., Califf, R. M., Cheitlin, M. D., Hochman, J. S., Jones, R. H., Kereiakes, D., Kupersmith, J., Levin, T. N., et al. (2000) · Circulation · doi:10.1161/01.cir.102.10.1193 · Cited by 4,487
Neural Networks and the Bias/Variance Dilemma
Geman, S., Bienenstock, E., & Doursat, R. (1992) · Neural Computation · doi:10.1162/neco.1992.4.1.1 · Cited by 3,578
Rosen, R., Cappelleri, J., Smith, M., Lipsky, J., & Peña, B. (1999) · International Journal of Impotence Research · doi:10.1038/sj.ijir.3900472 · Cited by 3,053
Clinical versus mechanical prediction: a meta-analysis
Grove, W. M., Zald, D. H., Lebow, B. S., Snitz, B. E., & Nelson, C. (2000) · Psychological Assessment · doi:10.1037/1040-3590.12.1.19 · Cited by 1,640
Clinical Prediction Rules: Applications and Methodological Standards
Wasson, J. H., Sox, H. C., Neff, R. K., & Goldman, L. (1985) · New England Journal of Medicine · doi:10.1056/nejm198509263131306 · Cited by 1,357
Self-citation
Metadata
- Authors
- Goldman, L., Weinberg, M., Weisberg, M., Olshen, R., Cook, E. F., Sargent, R. K., Lamas, G. A., Dennis, C., Wilson, C., Deckelbaum, L., Fineberg, H., Stiratelli, R., & Hospital*, T. M. H. S. A. Y. H. H. A. B. A. W.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1982-09-02
- Volume
- 307
- Issue
- 10
- Pages
- 588-596
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2078322828
- Cited by
- 502
- References
- 12
- FWCI
- 87.68
- Type
- journal article
- Language
- en
- Open access
- closed
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain. https://app.cochat.ai/papers/10.1056/nejm198209023071004
- The paper
- Goldman, L., Weinberg, M., Weisberg, M., Olshen, R., Cook, E. F., Sargent, R. K., Lamas, G. A., Dennis, C., Wilson, C., Deckelbaum, L., Fineberg, H., Stiratelli, R., & Hospital*, T. M. H. S. A. Y. H. H. A. B. A. W. (1982). A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain. New England Journal of Medicine. https://doi.org/10.1056/nejm198209023071004
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.