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Cited by 217

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Cardiopulmonary exercise testing as a risk assessment method in non cardio‐pulmonary surgery: a systematic review

Smith, T. B., Stonell, C., Purkayastha, S., Paraskevas, P.·2009·Anaesthesia

Abstract

Summary: This study reviews the predictive value of maximum oxygen consumption ( ) and anaerobic threshold, obtained through cardiopulmonary exercise testing, in calculating peri‐operative morbidity and mortality in non‐cardiopulmonary thoraco‐abdominal surgery. A literature review provided nine studies that investigated either one or both of these two variables across a wide range of surgical procedures. Six of the seven studies that reported sufficiently detailed results on peak oxygen consumption and four of the six studies that reported sufficiently detailed results on anaerobic threshold found them to be significant predictors. We conclude that peak oxygen consumption and possibly anaerobic threshold are valid predictors of peri‐operative morbidity and mortality in non‐cardiopulmonary thoraco‐abdominal surgery. These indicators could potentially provide a means of allocating increased care to high‐risk patients.

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Metadata

Authors
Smith, T. B., Stonell, C., Purkayastha, S., & Paraskevas, P.
Venue
Anaesthesia
Publisher
Wiley
Published
2009-07-08
Volume
64
Issue
8
Pages
883-893
ISSN
  • 0003-2409 (ISSN-L)
  • 1365-2044
OpenAlex
W2015372526
Cited by
217
References
1
FWCI
1.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cardiopulmonary exercise testing as a risk assessment method in non cardio‐pulmonary surgery: a systematic review. https://app.cochat.ai/papers/10.1111/j.1365-2044.2009.05983.x
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Smith, T. B., Stonell, C., Purkayastha, S., & Paraskevas, P. (2009). Cardiopulmonary exercise testing as a risk assessment method in non cardio‐pulmonary surgery: a systematic review. Anaesthesia. https://doi.org/10.1111/j.1365-2044.2009.05983.x

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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.