Literature DB >> 27792044

Relationship between Intraoperative Hypotension, Defined by Either Reduction from Baseline or Absolute Thresholds, and Acute Kidney and Myocardial Injury after Noncardiac Surgery: A Retrospective Cohort Analysis.

Vafi Salmasi1, Kamal Maheshwari, Dongsheng Yang, Edward J Mascha, Asha Singh, Daniel I Sessler, Andrea Kurz.   

Abstract

BACKGROUND: How best to characterize intraoperative hypotension remains unclear. Thus, the authors assessed the relationship between myocardial and kidney injury and intraoperative absolute (mean arterial pressure [MAP]) and relative (reduction from preoperative pressure) MAP thresholds.
METHODS: The authors characterized hypotension by the lowest MAP below various absolute and relative thresholds for cumulative 1, 3, 5, or 10 min and also time-weighted average below various absolute or relative MAP thresholds. The authors modeled each relationship using logistic regression. The authors further evaluated whether the relationships between intraoperative hypotension and either myocardial or kidney injury depended on baseline MAP. Finally, the authors compared the strength of associations between absolute and relative thresholds on myocardial and kidney injury using C statistics.
RESULTS: MAP below absolute thresholds of 65 mmHg or relative thresholds of 20% were progressively related to both myocardial and kidney injury. At any given threshold, prolonged exposure was associated with increased odds. There were no clinically important interactions between preoperative blood pressures and the relationship between hypotension and myocardial or kidney injury at intraoperative mean arterial blood pressures less than 65 mmHg. Absolute and relative thresholds had comparable ability to discriminate patients with myocardial or kidney injury from those without.
CONCLUSIONS: The associations based on relative thresholds were no stronger than those based on absolute thresholds. Furthermore, there was no clinically important interaction with preoperative pressure. Anesthetic management can thus be based on intraoperative pressures without regard to preoperative pressure.

Entities:  

Mesh:

Year:  2017        PMID: 27792044     DOI: 10.1097/ALN.0000000000001432

Source DB:  PubMed          Journal:  Anesthesiology        ISSN: 0003-3022            Impact factor:   7.892


  151 in total

1.  Closed-loop vasopressor control: in-silico study of robustness against pharmacodynamic variability.

Authors:  Joseph Rinehart; Alexandre Joosten; Michael Ma; Michael-David Calderon; Maxime Cannesson
Journal:  J Clin Monit Comput       Date:  2018-12-11       Impact factor: 2.502

2.  [Principles and pitfalls of arterial blood pressure measurement].

Authors:  A S Meidert; J Briegel; B Saugel
Journal:  Anaesthesist       Date:  2019-09       Impact factor: 1.041

3.  The future of intraoperative blood pressure management.

Authors:  Frederic Michard; Ngai Liu; Andrea Kurz
Journal:  J Clin Monit Comput       Date:  2017-02-07       Impact factor: 2.502

4.  [Choosing wisely in anesthesia : An important step in quality optimization].

Authors:  R Rossaint; M Coburn
Journal:  Anaesthesist       Date:  2017-09       Impact factor: 1.041

5.  Error-checking intraoperative arterial line blood pressures.

Authors:  Charles Huanghong Du; David Glick; Avery Tung
Journal:  J Clin Monit Comput       Date:  2018-06-05       Impact factor: 2.502

Review 6.  Perioperative myocardial injury and the contribution of hypotension.

Authors:  Daniel I Sessler; Ashish K Khanna
Journal:  Intensive Care Med       Date:  2018-06-04       Impact factor: 17.440

Review 7.  [Perioperative fluid management].

Authors:  B E Wellge; C J Trepte; C Zöllner; J R Izbicki; M Bockhorn
Journal:  Chirurg       Date:  2020-02       Impact factor: 0.955

Review 8.  Anaesthesia during oesophagectomy.

Authors:  Denise P Veelo; Bart F Geerts
Journal:  J Thorac Dis       Date:  2017-07       Impact factor: 2.895

Review 9.  Optimal Perioperative Blood Pressure Management.

Authors:  Senthil Packiasabapathy K; Balachundhar Subramaniam
Journal:  Adv Anesth       Date:  2018-09-24

10.  Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial.

Authors:  Marije Wijnberge; Bart F Geerts; Liselotte Hol; Nikki Lemmers; Marijn P Mulder; Patrick Berge; Jimmy Schenk; Lotte E Terwindt; Markus W Hollmann; Alexander P Vlaar; Denise P Veelo
Journal:  JAMA       Date:  2020-03-17       Impact factor: 56.272

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