Incidence and prediction of intraoperative and postoperative cardiac arrest requiring cardiopulmonary resuscitation and 30-day mortality in non-cardiac surgical patients


Autoři: Heiko A. Kaiser aff001;  Nahel N. Saied aff003;  Andreas S. Kokoefer aff001;  Lina Saffour aff001;  Jonathan K. Zoller aff001;  Mohammad A. Helwani aff001
Působiště autorů: Department of Anesthesiology, Washington University, St. Louis, Missouri, United States of America aff001;  Department of Anesthesiology and Pain Medicine; Inselspital, Bern University Hospital; University of Bern, Freiburgstrasse, Bern, Switzerland aff002;  Department of Anesthesiology and Critical Care, University of Arkansas Medical Sciences, Little Rock, Arkansas, United States of America aff003;  Department of Anesthesiology, Perioperative Care and Intensive Care Medicine, Paracelsus Medical University Salzburg, Strubergasse, Salzburg, Austria aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225939

Souhrn

Background

The incidence, prediction and mortality outcomes of intraoperative and postoperative cardiac arrest requiring cardiopulmonary resuscitation (CPR) in surgical patients are under investigated and have not been studied concurrently in a single study.

Methods

A retrospective cohort study was conducted using the American College of Surgeons National Surgical Quality Improvement Program data between 2008 and 2012. Firth’s penalized logistic regression was used to study the incidence and identify risk factors for intra- and postoperative CPR and 30-day mortality. simplified prediction model was constructed and internally validated to predict the studied outcomes.

Results

Among about 1.86 million non-cardiac operations, the incidence rate of intraoperative CPR was 0.03%, and for postoperative CPR was 0.33%. The 30-day mortality incidence rate was 1.25%. The incidence rate of events decreased overtime between 2008–2012. Of the 29 potential predictors, 14 were significant for intraoperative CPR, 23 for postoperative CPR, and 25 for 30-day mortality. The five strongest predictors (highest odd ratios) of intraoperative CPR were the American Society of Anesthesiologists (ASA) physical status, Systemic Inflammatory Response Syndrome (SIRS)/sepsis, surgery type, urgent/emergency case and anesthesia technique. Intraoperative CPR, ASA, age, functional status and end stage renal disease were the most significant predictors for postoperative CPR. The most significant predictors of 30-day mortality were ASA, age, functional status, SIRS/sepsis, and disseminated cancer. The predictions with the simplified five-factor model performed well and was comparable to the full prediction model. Postoperative cardiac arrest requiring CPR, compared to intraoperative, was associated with much higher mortality.

Conclusions

The incidence of cardiac arrest requiring CPR in surgical patients decreased overtime. Risk factors for intraoperative CPR, postoperative CPR and perioperative mortality are overlapped. We proposed a simplified approach compromised of five-factor model to identify patients at high risk. Postoperative, compare to intraoperative, cardiac arrest requiring CPR was associated with much higher mortality.

Klíčová slova:

Anesthesia – Cardiac arrest – Otolaryngological procedures – Plastic surgery and reconstructive techniques – Sepsis – Surgical and invasive medical procedures – Surgical oncology – Vascular surgery


Zdroje

1. Merchant RM, Yang L, Becker LB, Berg RA, Nadkarni V, Nichol G, et al. Incidence of treated cardiac arrest in hospitalized patients in the United States. Critical Care Medicine. 2011;39(11):2401–6. doi: 10.1097/CCM.0b013e3182257459 21705896

2. Kazaure HS, Roman SA, Rosenthal RA, Sosa JA. Cardiac arrest among surgical patients: an analysis of incidence, patient characteristics, and outcomes in ACS-NSQIP. JAMA surgery. 2013;148(1):14–21. doi: 10.1001/jamasurg.2013.671 23324834.

3. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Bmj. 2007;335(7624):806–8. doi: 10.1136/bmj.39335.541782.AD 17947786

4. H D Jr. Applied Logistic Regression. Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2013.

5. King GZL. Logistic Regression in Rare Events Data. Political Analysis. 2001;9. Epub 163.

6. D. F. Bias reduction of maximum likelihood estimates: Biometrika; 1993.

7. Heinze G PM, Dunkler D, Southworth H. logistf: Firth’s bias reduced logistic regression: R package version 2013; 2013.

8. Harrell FE Jr HMJ. Package "Hmisc."2016.

9. Ofoma UR, Basnet S, Berger A, Kirchner HL, Girotra S, Investigators AHAGWTG-R. Trends in Survival After In-Hospital Cardiac Arrest During Nights and Weekends. Journal of the American College of Cardiology. 2018;71(4):402–11. doi: 10.1016/j.jacc.2017.11.043 29389356

10. Bainbridge D, Martin J, Arango M, Cheng D, Evidence-based Peri-operative Clinical Outcomes Research G. Perioperative and anaesthetic-related mortality in developed and developing countries: a systematic review and meta-analysis. Lancet. 2012;380(9847):1075–81. doi: 10.1016/S0140-6736(12)60990-8 22998717.

11. Ellis SJ, Newland MC, Simonson JA, Peters KR, Romberger DJ, Mercer DW, et al. Anesthesia-related cardiac arrest. Anesthesiology. 2014;120(4):829–38. doi: 10.1097/ALN.0000000000000153 24496124.

12. Nunnally ME, O’Connor MF, Kordylewski H, Westlake B, Dutton RP. The incidence and risk factors for perioperative cardiac arrest observed in the national anesthesia clinical outcomes registry. Anesthesia & Analgesia. 2015;120(2):364–70. doi: 10.1213/ANE.0000000000000527 25390278.

13. Hohn A, Machatschek J-N, Franklin J, Padosch SA. Incidence and risk factors of anaesthesia-related perioperative cardiac arrest: A 6-year observational study from a tertiary care university hospital. European journal of anaesthesiology. 2018;35(4):266–72. doi: 10.1097/EJA.0000000000000685 28922339.

14. Fleisher LA, Fleischmann KE, Auerbach AD, Barnason SA, Beckman JA, Bozkurt B, et al. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;130(24):2215–45. doi: 10.1161/CIR.0000000000000105 25085962.

15. Helwani MA, Avidan MS, Ben Abdallah A, Kaiser DJ, Clohisy JC, Hall BL, et al. Effects of regional versus general anesthesia on outcomes after total hip arthroplasty: a retrospective propensity-matched cohort study. The Journal of bone and joint surgery American volume. 2015;97(3):186–93. doi: 10.2106/JBJS.N.00612 25653318.

16. Saied NN, Helwani MA, Weavind LM, Shi Y, Shotwell MS, Pandharipande PP. Effect of anaesthesia type on postoperative mortality and morbidities: a matched analysis of the NSQIP database. British Journal of Anaesthesia. 2017;118(1):105–11. doi: 10.1093/bja/aew383 28039248.

17. Ramachandran SK, Mhyre J, Kheterpal S, Christensen RE, Tallman K, Morris M, et al. Predictors of survival from perioperative cardiopulmonary arrests: a retrospective analysis of 2,524 events from the Get With The Guidelines-Resuscitation registry. Anesthesiology. 2013;119(6):1322–39. doi: 10.1097/ALN.0b013e318289bafe 23838723


Článek vyšel v časopise

PLOS One


2020 Číslo 1