The DOI matches its Crossref record.
Combining Clinical and Thallium Data Optimizes Preoperative Assessment of Cardiac Risk before Major Vascular Surgery
Abstract
STUDY OBJECTIVE: To determine whether clinical markers and preoperative dipyridamole-thallium imaging are both useful in predicting ischemic events after vascular surgery. DESIGN: Retrospective, observational study. SETTING: University medical center. PATIENTS: Two hundred fifty-four consecutive patients referred to a nuclear cardiology laboratory before surgery. Forty-four patients had surgery cancelled or postponed after clinical evaluation and dipyridamole-thallium imaging. Surgery was not confirmed for ten. Two hundred patients receiving prompt vascular surgery were the study group. MEASUREMENTS AND MAIN RESULTS: Thirty patients (15%) had early postoperative cardiac ischemic events, with cardiac death in 6 (3%) and nonfatal myocardial infarction in 9 (4.5%). Logistic regression identified five clinical predictors (Q waves, history of ventricular ectopic activity, diabetes, advanced age, angina) and two dipyridamole-thallium predictors of postoperative events. Of patients with none of the clinical variables (n = 64), only 2 (3.1%; 95% CI, 0% to 8%) had ischemic events with no cardiac deaths. Ten of twenty (50%; 95% CI, 29% to 71%) patients with three or more clinical markers had events. Eighteen of one hundred sixteen (15.5%; 95% CI, 7% to 21%) patients with either 1 or 2 clinical predictors had events. Within this group, 2 of 62 (3.2%; 95% CI, 0% to 8%) patients without thallium redistribution had events compared with 16 events in 54 patients (29.6%; 95% CI, 16% to 44%) with thallium redistribution. The multivariate model using both clinical and thallium variables showed significantly higher specificity at equivalent sensitivity levels than models using either clinical or thallium variables alone. CONCLUSIONS: Preoperative dipyridamole-thallium imaging appears most useful to stratify vascular patients determined to be at intermediate risk by clinical evaluation. For patients with one or two clinical predictors, thallium redistribution correlates with substantial change in probability of events. For nearly half the patients, however, thallium imaging may have been unnecessary because of very high or low cardiac risk predicted by clinical information alone.
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
Cited by
Scanlon, P. J., Faxon, D. P., Audet, A.-M., Carabello, B., Dehmer, G. J., Eagle, K. A., Legako, R. D., Leon, D. F., Murray, J. A., Nissen, S. E., et al. (1999) · Journal of the American College of Cardiology · doi:10.1016/s0735-1097(99)00126-6 · Cited by 1,123
Self-citationMangano, D. T., Browner, W. S., Hollenberg, M., London, M. J., Tubau, J. F., & Tateo, I. M. (1990) · New England Journal of Medicine · doi:10.1056/nejm199012273232601 · Cited by 992
Identifying and grading factors that modify the outcome of endovascular aortic aneurysm repair
Chaikof, E. L., Fillinger, M. F., Matsumura, J. S., Rutherford, R. B., White, G. H., Blankensteijn, J. D., Bernhard, V. M., Harris, P. L., Kent, K. C., May, J., et al. (2002) · Journal of Vascular Surgery · doi:10.1067/mva.2002.123991 · Cited by 629
Fleisher, L. A., Beckman, J. A., Brown, K. A., Calkins, H., Chaikof, E. L., Fleischmann, K. E., Freeman, W. K., Froehlich, J. B., Kasper, E. K., Kersten, J. R., et al. (2007) · Circulation · doi:10.1161/circulationaha.107.185699 · Cited by 587
Committee Members, Eagle, K. A., Berger, P. B., Calkins, H., Chaitman, B. R., Ewy, G. A., Fleischmann, K. E., Fleisher, L. A., Froehlich, J. B., Gusberg, R. J., et al. (2002) · Circulation · doi:10.1161/circ.105.10.1257 · Cited by 412
Self-citation
Metadata
- Authors
- Eagle, K. A., Coley, C. M., Newell, J. B., Brewster, D. C., Darling, R. C., Strauss, H. W., Guiney, T. E., & Boucher, C. A.
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 1989-06-01
- Volume
- 110
- Issue
- 11
- Pages
- 859-866
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W2073429865
- Cited by
- 728
- References
- 0
- FWCI
- 29.76
- 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: Combining Clinical and Thallium Data Optimizes Preoperative Assessment of Cardiac Risk before Major Vascular Surgery. https://app.cochat.ai/papers/10.7326/0003-4819-110-11-859
- The paper
- Eagle, K. A., Coley, C. M., Newell, J. B., Brewster, D. C., Darling, R. C., Strauss, H. W., Guiney, T. E., & Boucher, C. A. (1989). Combining Clinical and Thallium Data Optimizes Preoperative Assessment of Cardiac Risk before Major Vascular Surgery. Annals of Internal Medicine. https://doi.org/10.7326/0003-4819-110-11-859
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.