Literature DB >> 14980900

The incidence and prediction of automatically detected intraoperative cardiovascular events in noncardiac surgery.

Rainer Röhrig1, Axel Junger, Bernd Hartmann, Joachim Klasen, Lorenzo Quinzio, Andreas Jost, Matthias Benson, Gunter Hempelmann.   

Abstract

UNLABELLED: The objective of this study was to evaluate prognostic models for quality assurance purposes in predicting automatically detected intraoperative cardiovascular events (CVE) in 58458 patients undergoing noncardiac surgery. To this end, we assessed the performance of two established models for risk assessment in anesthesia, the Revised Cardiac Risk Index (RCRI) and the ASA physical status classification. We then developed two new models. CVEs were detected from the database of an electronic anesthesia record-keeping system. Logistic regression was used to build a complex and a simple predictive model. Performance of the prognostic models was assessed using analysis of discrimination and calibration. In 5249 patients (17.8%) of the evaluation (n = 29437) and 5031 patients (17.3%) of the validation cohorts (n = 29021), a minimum of one CVE was detected. CVEs were associated with significantly more frequent hospital mortality (2.1% versus 1.0%; P < 0.01). The new models demonstrated good discriminative power, with an area under the receiver operating characteristic curve (AUC) of 0.709 and 0.707 respectively. Discrimination of the ASA classification (AUC 0.647) and the RCRI (AUC 0.620) were less. Neither the two new models nor ASA classification nor the RCRI showed acceptable calibration. ASA classification and the RCRI alone both proved unsuitable for the prediction of intraoperative CVEs. IMPLICATIONS: The objective of this study was to evaluate prognostic models for quality assurance purposes to predict the occurrence of automatically detected intraoperative cardiovascular events in 58,458 patients undergoing noncardiac surgery. Two newly developed models showed good discrimination but, because of reduced calibration, their clinical use is limited. The ASA physical status classification and the Revised Cardiac Risk Index are unsuitable for the prediction of intraoperative cardiovascular events.

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Year:  2004        PMID: 14980900     DOI: 10.1213/01.ane.0000103262.26387.9c

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  12 in total

Review 1.  [Minimizing perioperative risk - an interdisciplinary effort].

Authors:  Matthias Bock; Christian J Wiedermann
Journal:  Wien Med Wochenschr       Date:  2008

2.  A meta-analysis of the predictive accuracy of postoperative mortality using the American Society of Anesthesiologists' physical status classification system.

Authors:  Chieh Yang Koo; Joseph A Hyder; Jonathan P Wanderer; Matthias Eikermann; Satya Krishna Ramachandran
Journal:  World J Surg       Date:  2015-01       Impact factor: 3.352

Review 3.  Anesthesia information management systems: a review of functionality and installation considerations.

Authors:  Jesse M Ehrenfeld; Mohamed A Rehman
Journal:  J Clin Monit Comput       Date:  2010-08-24       Impact factor: 2.502

Review 4.  Using real-time clinical decision support to improve performance on perioperative quality and process measures.

Authors:  Anthony Chau; Jesse M Ehrenfeld
Journal:  Anesthesiol Clin       Date:  2011-03

Review 5.  Minimizing cardiac risk in perioperative practice - interdisciplinary pharmacological approaches.

Authors:  Matthias Bock; Christian J Wiedermann; Johann Motsch; Gerhard Fritsch; Markus Paulmichl
Journal:  Wien Klin Wochenschr       Date:  2011-06-22       Impact factor: 1.704

Review 6.  The comparative and added prognostic value of biomarkers to the Revised Cardiac Risk Index for preoperative prediction of major adverse cardiac events and all-cause mortality in patients who undergo noncardiac surgery.

Authors:  Lisette M Vernooij; Wilton A van Klei; Karel Gm Moons; Toshihiko Takada; Judith van Waes; Johanna Aag Damen
Journal:  Cochrane Database Syst Rev       Date:  2021-12-21

7.  Does the Surgical Apgar Score measure intraoperative performance?

Authors:  Scott E Regenbogen; R Todd Lancaster; Stuart R Lipsitz; Caprice C Greenberg; Matthew M Hutter; Atul A Gawande
Journal:  Ann Surg       Date:  2008-08       Impact factor: 12.969

8.  Risk factors for intraoperative hypotension during thyroid surgery.

Authors:  Nevena Kalezic; Marina Stojanovic; Nebojsa Ladjevic; Dejan Markovic; Ivan Paunovic; Ivan Palibrk; Biljana Milicic; Vera Sabljak; Vesna Antonijevic; Branislava Ivanovic; Djordje Ugrinovic; Vladan Zivaljevic
Journal:  Med Sci Monit       Date:  2013-04-03

9.  Corrected incidences of co-morbidities - a statistical approach for risk-assessment in anesthesia using an AIMS.

Authors:  Rainer Röhrig; Bernd Hartmann; Axel Junger; Joachim Klasen; Dominik Brammen; Florian Brenck; Andreas Jost; Gunter Hempelmann
Journal:  J Clin Monit Comput       Date:  2007-04-05       Impact factor: 1.977

10.  Determinants of postoperative acute kidney injury.

Authors:  Fernando José Abelha; Miguela Botelho; Vera Fernandes; Henrique Barros
Journal:  Crit Care       Date:  2009-05-22       Impact factor: 9.097

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