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Perioperative Medicine  |   January 2017
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
Author Notes
  • From the Departments of Outcomes Research and General Anesthesiology (V.S., K.M., D.I.S., A.K.), Departments of Quantitative Health Sciences and Outcomes Research (D.Y., E.J.M.), and Anesthesiology Institute, Cleveland Clinic, Cleveland, Ohio (A.S.).
  • This article is featured in “This Month in Anesthesiology,” page 1A.
    This article is featured in “This Month in Anesthesiology,” page 1A.×
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  • Submitted for publication April 22, 2016. Accepted for publication September 23, 2016.
    Submitted for publication April 22, 2016. Accepted for publication September 23, 2016.×
  • Address correspondence to Dr. Sessler: Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, 9500 Euclid Ave, P77, Cleveland, Ohio 44195. DS@OR.org. This article may be accessed for personal use at no charge through the Journal Web site, www.anesthesiology.org.
Article Information
Perioperative Medicine / Clinical Science / Cardiovascular Anesthesia / Renal and Urinary Systems / Electrolyte Balance / Trauma / Burn Care
Perioperative Medicine   |   January 2017
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
Anesthesiology 1 2017, Vol.126, 47-65. doi:10.1097/ALN.0000000000001432
Anesthesiology 1 2017, Vol.126, 47-65. doi:10.1097/ALN.0000000000001432
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.

What We Already Know about This Topic
  • Previous studies have demonstrated associations between low mean arterial pressure (MAP) and organ injury, with hypotension defined in terms of minutes or integrated pressures below various absolute thresholds.

  • This study assessed the relationship between myocardial and kidney injury and intraoperative absolute (intraoperative MAP) and relative (reduction from preoperative pressure) MAP thresholds using retrospective data from a single institution.

What This Article Tells Us That Is New
  • The associations based on relative mean arterial pressure thresholds were no stronger than those based on absolute thresholds. Furthermore, there was no clinically important interaction with preoperative pressure. These data suggest that anesthetic management can thus be based on intraoperative pressures without regard to preoperative pressure.

THE perioperative period is characterized by hemodynamic instability. Various degrees of hypotension are common during anesthesia and surgery and may cause organ ischemia. For example, hypotension contributes to oxygen supply–demand mismatch, which appears to be an important cause of postoperative myocardial infarction.1–3  Furthermore, ischemia and reperfusion may contribute to postoperative acute kidney injury (AKI).4–10  Myocardial perfusion is dependent on pressure gradient created by diastolic blood pressure11 ; vasomotor responses and regional ischemia in response to decreased blood pressure and cardiac output also contribute to ischemic renal injury.12,13 
A systematic review of interventions to decrease the incidence of postoperative AKI demonstrated that avoiding hypotension reduced the incidence of AKI.14  Consistent with the theory that intraoperative hypotension contributes to organ injury, hypotension, defined in various ways, is weakly associated with AKI8,10  and strongly associated with myocardial infarction8,15  and death.9,16 
How best to characterize hypotension remains unclear, and there is no universal definition of hypotension. In a systematic review, for example, Bijker et al.17  found 140 definitions for hypotension in 130 articles. A consequence was that the incidence of intraoperative hypotension ranged from 5 to 99% depending on the selected definition.
Several recent studies report associations between low mean arterial pressure (MAP) and organ injury, with hypotension defined in terms of minutes or integrated pressures below various absolute thresholds.8–10,15  This approach differs from classical anesthesia teaching, which suggests keeping blood pressure within a relative 20% of preoperative values, apparently based on the theory that hypertensive patients require higher than normal pressures to adequately perfuse organs habituated to high pressures. Despite the frequency of this recommendation, it does not appear to be based on credible outcome evidence. Which characterization of blood pressure, absolute versus relative hypotension, is most related to organ injury remains unknown.
Therefore, we assessed the relationship between various absolute and relative characterizations of hypotension and myocardial injury after noncardiac surgery (MINS)18  and AKI in adults having inpatient surgery. Absolute thresholds were characterized by the lowest MAP maintained for various durations and by time under various MAP thresholds. Relative hypotension was characterized by maximum percentage MAP decrease from baseline maintained for various durations and by time under various percentage reductions from baseline. We then evaluated the interaction between preoperative MAP and the relationships between intraoperative hypotension and MINS or AKI. Finally, we determined whether absolute or relative characterizations best predict MINS and AKI.
Materials and Methods
We conducted a retrospective cohort study using data from the Cleveland Clinic Perioperative Health Documentation System and Epic, electronic medical record-based registries of noncardiac surgery patients who had undergone surgery between January 6, 2005, and March 1, 2014, at the Cleveland Clinic, Cleveland, Ohio.
Inclusion criteria were as follows: (1) adults who had inpatient noncardiac surgery between January 6, 2005, and March 1, 2014; (2) preoperative and at least one postoperative serum creatinine measurement available within the first 7 postoperative days; (3) blood pressure recorded in the preanesthesia care evaluation clinic or other preoperative appointments within 6 months before surgery.
Exclusion criteria were as follows: (1) patients with chronic kidney disease defined as preoperative estimated glomerular filtration rate of less than 60 ml × min−1 × 1.73 m−2 or patients who were on dialysis; (2) urologic procedures including relief of urinary obstruction (International Classification of Diseases, Ninth Revision [ICD-9] codes of 5501, 5502, 5503, 5504, 5511, 5512, 560, 570, 5741, 5749, 602, 6021, 6029, 6096, 6097, 603, 604, 605, 6061, 6062, and 6069), nephrectomy (ICD-9 codes of 554, 5551, 5552, 5553, and 5554), or renal transplantation (ICD-9 codes of 5561 and 5569); (3) patients who had anesthesia for less than 60 min or missing baseline variables; (4) patients with invalid or unavailable data for more than 10 consecutive minutes.
Outcomes
  1. MINS was defined as at least one increased postoperative value of either fourth-generation troponin T or creatine kinase-MB above the upper limit of normal in the 7 days after operation. The upper limit of normal was defined as 0.03 ng/ml for troponin T18 and 8.8 ng/ml for creatine kinase-MB.3  Eligible patients without postoperative cardiac enzyme determinations were assumed not to have acute myocardial injury.

  2. Postoperative AKI was defined by increases in serum creatinine between preoperative and postoperative values. Preoperative creatinine was taken to be the last before surgery. Postoperative creatinine was taken to be the highest concentration measured within 7 postoperative days. According to the Acute Kidney Injury Network definition, patients were considered to have AKI if the postoperative value was either more than 1.5-fold or more than 0.3 mg/dl before surgery.8 

Statistical Methods
MAP and Artifact Removing Algorithm.
Intraoperative MAPs recorded in the Perioperative Health Documentation System cannot be modified by clinicians, but can be identified as artifactual. Invasive pressures were recorded at 1-min intervals; noninvasive pressures were recorded at 1- to 5-min intervals. We removed artifacts using the following rules, in order: (1) blood pressures documented as artifacts; (2) pressures out-of-range defined by (a) SBP greater than or equal to 300 or SBP less than or equal to 20 mmHg, (b) SBP less than or equal to DBP + 5 mmHg, or (c) DBP less than or equal to 5 mmHg or DBP greater than or equal to 225 mmHg; (3) abrupt changes defined by SBP change greater than or equal to 80 mmHg within 1 min in either direction or abrupt SBP changes greater than or equal to 40 mmHg within 2 min in both directions. Pressures between measurements were linearly interpolated.
Baseline MAP is described as the average of all MAP readings in the 6 months before surgery, excluding measurements during a hospital stay. Anesthesia time was defined as the interval between induction and emergence.
Confounding Variables.
Potentially confounding variables are listed in table 1. We defined preexisting medical conditions using ICD-9 billing codes and included only those fulfilling at least one of the following: (1) appeared in the patient “problem list” with a date preceding the date of surgery; (2) appeared in an ICD-9 list before the index surgery; or (3) were flagged as a chronic ICD-9 condition based on Healthcare Cost and Utilization Project definitions. Because there were many types of surgical procedures, we characterized each procedure code into one of 231 clinically meaningful categories using the Agency for Healthcare Research and Quality’s Clinical Classifications Software for Services and Procedures.19  We then aggregated low-frequency event or nonevent categories (n < 10) into one group and used that as the reference group (a low-risk group).20 
Table 1.
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS×
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Table 1.
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS×
×
Determining MAP Thresholds.
We first determined the absolute and relative (percent below baseline) thresholds below which MINS and AKI began to increase. Specifically, we assessed the relationships between MINS or AKI and the lowest MAP or the lowest percent decrease from baseline for a cumulative case total of 1, 3, 5, and 10 min, and time-weighted average under absolute thresholds (i.e., less than 55, less than 60, less than 65, less than 70, less than 75 mmHg) or relative thresholds (i.e., greater than 10%, greater than 15%, greater than 20%, greater than 25%, greater than 30% decrease from baseline).
We first assessed the univariable relationship between each MAP threshold and MINS and AKI using moving-average smoothing plots. Relationships were then studied further using multivariable logistic regression to adjust for confounding and model the relationships; linearity between each MAP exposure and response was modeled by a restricted cubic spline function with three knots located at 10th, 50th, and 90th percentiles. The univariable moving-average plots and multivariable smoothed cubic spline curves were studied to find optimal thresholds based on the data. We further evaluated interactions between baseline MAP and the relationship between exposure and outcome.
Deriving MAP Exposures.
Based on inspection of exposure versus outcome curves, we determined that absolute thresholds of 65 mmHg and lower and relative thresholds of 20% or more decrease from the baseline MAP were associated with the increased risk of both MINS and AKI. We then defined our main absolute and relative exposures to be (1) number of minutes under each threshold and (2) area under each threshold. Since all relationships were found to be nonlinear, we categorized patients as belonging to either a reference group who spent no time under a given threshold or to one of four groups based on quartiles of nonzero time spent under the threshold.
Specifically, we defined the absolute MAP reference group as patients whose intraoperative MAPs were never less than 65 mmHg. For the remaining patients, we counted the number of minutes within the lowest achieved category per patient: less than 50, 50 to 55, 55 to 60, and 60 to 65 mmHg. That is, each patient was assigned uniquely to one of the four hypotension categories. We then categorized cumulative minutes of exposure into 1, 2 to 4, or greater than equal to 5 min for a total of 12 groups (i.e., four pressure ranges by three durations) and compared each to the reference group.
We similarly defined the relative MAP reference group as patients whose intraoperative MAPs were never more than 20% below the preoperative reference pressure. For the remaining patients, we counted the number of minutes within the lowest achieved category per patient: 20 to 30%, 30 to 40%, 40 to 50%, and greater than 50% below baseline. Thus, each patient was again assigned uniquely to one of 12 groups (i.e., four pressure ranges by three durations) and compared each to the reference group.
Multivariable logistic regression was used to assess the association between the above MAP exposures and postoperative MINS or AKI. All potentially confounding variables listed in table 1 were forced into the models regardless of statistical significance. Bonferroni correction was used to adjust for four main comparisons within each exposure of interest, with P < 0.0125 (i.e., P < 0.05/4 = 0.0125) considered statistically significant. Interactions between baseline MAP and exposures were considered significant if P < 0.05. All analyses were performed with the use of SAS software, version 9.4 (SAS Institute, USA).
Sample Size Considerations.
We expected to have between 50,000 and 150,000 patients meeting all study criteria. With at least 50,000 patients and the incidence of MINS or AKI of 2% or more, we had good statistical power (80% or more) to detect moderately small odds ratios, especially given the continuous/ordinal nature of the predictor variables.
Results
Of 164,514 patients having noncardiac surgery between 2005 and 2015, analysis included 57,315 patients who met our inclusion and exclusion criteria (fig. 1). Different subsets of these patients were included in studies by Walsh et al.8  and Mascha et al.16  The overall incidence of MINS was 3.1% and of AKI was 5.6% among qualified patients. Only 8,558 patients (15%) had postoperative troponin tests, and we assumed that patients without the test did not have MINS.
Fig. 1.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
Fig. 1.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
×
Nearly all demographic, medical history, procedural, medicine, preoperative, and intraoperative factors were associated with both MINS and AKI (table 1). Descriptive statistics for baseline MAP and all MAP exposures are displayed in table A1. Baseline MAP was based on a mean of 5 ± 3 values per patient in the 6 months before surgery. Average baseline MAP was 93 ± 10 mmHg; preinduction MAP averaged 101 ± 16 mmHg, and intraoperative time-weighted average MAP was 84 ± 10 mmHg.
Univariable analyses showed that patients having postoperative MINS or AKI had higher time-weighted average, area under threshold, and number of minutes under all thresholds compared to those with no evidence of AKI or MINS (all P < 0.001; table 2).
Table 2.
Univariable Relationship between MAP Exposures and Outcomes
Univariable Relationship between MAP Exposures and Outcomes×
Univariable Relationship between MAP Exposures and Outcomes
Table 2.
Univariable Relationship between MAP Exposures and Outcomes
Univariable Relationship between MAP Exposures and Outcomes×
×
Univariable moving-average and multivariable spline smoothing plots for the lowest observed MAPs for a patient are shown for MINS in fig. 2 and for AKI in fig. 3. Odds for both MINS and AKI increased for decreasing thresholds of MAP less than 65 mmHg for any of 1, 3, 5, or 10 min. A relative MAP threshold of 20% below baseline was not an obvious change-point for AKI (fig. 3), but it was for MINS (fig. 2). We thus selected an absolute reference threshold of 65 mmHg and a relative reference threshold of 20% below baseline for further analysis.
Fig. 2.
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Fig. 2.
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 3.
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Fig. 3.
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
×
Increasing time-weighted average MAP under various absolute and relative thresholds was associated with increased odds of MINS (fig. 4) and AKI (fig. 5), both univariably and multivariably. Further, the relationships strengthened at lower thresholds. For example, the observed slope for less than 60 mmHg is steeper than that for less than 65 mmHg, and the observed slope for less than 25% below baseline is steeper than that for pressures less than 20% below baseline (figs. 4 and 5).
Fig. 4.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Fig. 4.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 5.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Fig. 5.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
×
There was no interaction between baseline MAP and the relationship between the TWA under various relative thresholds for either MINS or AKI. Furthermore, there was no interaction with TWA under absolute thresholds for AKI (all P > 0.40). There was some evidence of interaction between baseline MAP and the relationship between TWA under absolute thresholds and MINS (table 3). Investigating further, univariable moving-average and multivariable spline smoothing plots by quartile of baseline MAP showed that there were no clinically important interactions at MAPs less than 65 mmHg (fig. 6).
Table 3.
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*×
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Table 3.
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*×
×
Fig. 6.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
Fig. 6.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
×
Discriminative Ability
Using different absolute or relative thresholds did not increase discriminative ability, as evidenced by similar C-statistic values. The full multivariable model for MINS (table A2), including all baseline and intraoperative covariables mentioned in table 1, has a C statistic of 0.86. In contrast, blood pressure alone had a C statistic between 0.55 and 0.66. Whether hypotension exposure was defined by cumulative minutes of the lowest MAP (0.62 to 0.65) or duration under various thresholds (0.55 to 0.62), the C statistic values were essentially the same for absolute and relative exposures. There was thus no advantage to using relative thresholds for myocardial injury.
For AKI, the full multivariable model, including all baseline and intraoperative covariables mentioned in table 1, had a C statistic of 0.81 (table A3). In contrast, blood pressure alone had a C statistic between 0.54 and 0.59. Whether hypotension exposure was defined by cumulative minutes of lowest MAP or duration under various thresholds, the C statistic was nearly identical for absolute and relative thresholds. There was thus no advantage to using relative thresholds for AKI either.
Relationship between Exposure Categories and Outcomes
Time spent under the absolute threshold of MAP less than 65 mmHg had increased odds of MINS, with an odds ratio (OR; 98.75% CI) of 1.34 (1.06 to 1.68) for the third quartile and 1.60 (1.28 to 2.01) for the fourth quartile (table 4). Results were similar when hypotension exposure was characterized by area (rather than minutes) under absolute thresholds. In contrast, there were no significant associations between minutes or area under the relative threshold of 20% below baseline and MINS. Hypotension exposure was also characterized by various blood pressure ranges and exposure durations within each range. For instance, MAP less than 50 mmHg for at least 1 min or a 50% decrease from baseline for at least 1 min increased the odds of MINS after Bonferroni correction.
Table 4.
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
MINS: Multivariable Association with Absolute and Relative MAP Thresholds×
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
Table 4.
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
MINS: Multivariable Association with Absolute and Relative MAP Thresholds×
×
Time spent under the absolute threshold of MAP less than 65 mmHg had increased odds of AKI compared to patients never going less than 65 mmHg, with an OR (98.75% CI) of 1.20 (1.02 to 1.40) for the third quartile and 1.35 (1.14 to 1.58) for the fourth quartile (table 5). When hypotension exposure was characterized by area (rather than time) under absolute thresholds, odds were higher than reference only for the fourth quartile, with OR (98.75% CI) of 1.34 (1.15 to 1.58). For a relative threshold of 20% below baseline, again the fourth quartile had significantly higher odds of AKI with OR (98.75% CI) of 1.27 (1.01 to 1.61). The lowest hypotension exposure was also characterized by various blood pressure ranges and by exposure durations within each range. For instance, absolute categories of 50 to 55 mmHg for at least 1 min and less than 50 mmHg had higher odds of AKI compared to those never less than 65 mmHg. A relative decrease of greater than 50% from baseline MAP had higher odds of AKI compared to those never reaching less than 20% of baseline.
Table 5.
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds×
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
Table 5.
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds×
×
Discussion
We first characterized hypotension exposure by the lowest MAP maintained for various durations and by time under various absolute MAP thresholds. MAP less than 65 mmHg for greater than equal to 13 min (characterizing 50% of the patients who ever went less than 65 mmHg) was associated with significantly higher odds of myocardial and kidney injury. Injury was more common at lower absolute thresholds, and when hypotension was prolonged. At a MAP of 50 mmHg, for example, just 1 min significantly increased the risk for both myocardial and kidney injury.
Our results are broadly consistent with the results of previous reports. Based on previous studies, MAP less than absolute thresholds of 49 to 60 for various durations ranging from 1 to 30 min increases the risk of myocardial and kidney injury and mortality.8–10,15,16  Available analyses thus suggest that even short periods of hypotension below MAPs thresholds of 50 to 65 mmHg are associated with kidney and myocardial injury. While causality cannot be determined from analysis of purely observational data, all results suggest that anesthesiologists should avoid unnecessary hypotension. In this context, it is sobering that therapeutic hypotension was used for decades—often for nonessential reasons.
We also characterized hypotension exposure by time under various relative MAP thresholds. Injury was more common at lower absolute thresholds, and when hypotension was prolonged. For example, a cumulative time exceeding 90 min (highest quartile of patients) with MAP less than 20% below preoperative values was needed to increase the odds of kidney injury, and total minutes less than 20% was not significant for myocardial injury. When MAP was more than 50% below preoperative values, just 5 min significantly increased the risk for both myocardial and kidney injury.
Again, our results are broadly consistent with the results of previous reports. Monk et al.9  showed that blood pressure measurements less than 50% below baseline was associated with increased 30-day mortality although their analysis was limited in that one third of their patients lacked baseline blood pressures. Van Waes et al.15  showed that a relative decrease in MAP to values less than 40% below preinduction blood pressure for more than 30 min was associated with the increased incidence of myocardial injury. Available analyses thus suggest that sufficient time with pressures less than 20% or even short periods of hypotension to less than 40 to 50% below preoperative MAPs are associated with kidney and myocardial injury. The classical teaching that intraoperative pressures should be maintained within 20% of preoperative values thus appears justified.
The interaction between preoperative blood pressure and the relationship between intraoperative blood pressure and postoperative outcome was evaluated by Levin et al.21  They found that hypertensive patients had more intraoperative blood pressure lability and that lability decreased mortality. In our study, however, there was no interaction between baseline pressure and the relationship between intraoperative hypotension and AKI. Intraoperative hypotension was thus proportionately related to AKI over the entire range of preoperative pressures.
In contrast, there was a significant interaction between baseline pressure and the relationship between intraoperative pressure and myocardial injury. However, the interaction was only substantive at intraoperative MAPs exceeding 65 mmHg. In the clinically relevant range of hypotensive pressures less than 65 mmHg, there was no important interaction. Preoperative blood pressure thus had no important effect on the relationship between intraoperative hypotension and myocardial injury.
From a clinical perspective, our interaction analysis thus indicates that anesthesiologists can manage intraoperative blood pressure without reference to preoperative values—a conclusion that differs starkly from classical anesthesia teaching that patients with high preoperative pressures should be maintained at relatively high pressures throughout surgery. A caveat, of course, is that we evaluated only two organs. It remains possible that preoperative pressures do matter for the brain and other physiologic functions such as gut permeability.
A novel aspect of our study is comparison between absolute and relative thresholds. Both were predictive. However, there was no advantage to using relative over absolute thresholds for AKI or myocardial injury. Absolute thresholds are easier to use since a reliable baseline pressure is not required. Furthermore, absolute thresholds are far easier to incorporate into decision support systems that would not normally have access to individual preoperative reference values. Therefore, we conclude that clinicians can use absolute thresholds to guide intraoperative blood pressure management.
We defined myocardial injury on the basis of increased cardiac enzymes. However, cardiac enzymes were not routinely measured even in relatively high-risk patients during the study period. Consequently, our analysis was mostly based on clinically apparent myocardial infarctions, thus underestimating the actual incidence of myocardial injury by about a factor-of-three.1  Whether the relationships between hypotension and myocardial injury that we report apply comparably to silent injury remains unknown. However, the physiology is probably similar, suggesting that the relationships are probably similar.
As in any retrospective analysis, confounding and bias are concerns. For example, patients who experienced MINS or AKI were generally sicker and had more preoperative comorbidities. However, our large sample size and detailed registry allowed us to statistically adjust for many potential confounding factors. Our results are nonetheless surely somewhat degraded by both unknown and known but poorly characterized confounders. The extent to which either contributes is hard to assess.
About 60% of our patients had blood pressure measured oscillometrically at 1- to 5-min intervals. We linearly interpolated between measurements to provide reasonable estimates of intervening values, but is obviously less accurate than values from arterial catheters that were available at 1-min intervals. It seems unlikely that more frequent measurements would much change the harm thresholds we identified.
Conclusion
Pressures that until recently were considered clinically acceptable, for instance, a MAP of 65 mmHg, were associated with both myocardial and renal injuries. At lower pressures, the association was stronger and only brief exposures were required. Associations based on relative thresholds were no stronger than those based on absolute thresholds. Furthermore, there was no clinically important interaction with preoperative pressure. The extent to which the associations we observe are causal remains to be determined. But to the extent that they are, a strategy aimed at maintaining MAP above 65 mmHg appears to be as good as one based on the percentage reduction from baseline. This result is fortuitous because absolute thresholds are easier to use in that they do not require a reliable baseline pressure and can thus more easily be incorporated into decision support systems. While retrospective analyses cannot assess causality, our results suggest that maintaining intraoperative MAP greater than 65 mmHg may reduce the risk of AKI and myocardial injury—the leading cause of 30-day postoperative mortality.
Research Support
Support was provided solely from institutional and/or departmental sources.
Competing Interests
The authors declare no competing interests.
References
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Appendix
Table A1.
Summarized Statistics of MAP
Summarized Statistics of MAP×
Summarized Statistics of MAP
Table A1.
Summarized Statistics of MAP
Summarized Statistics of MAP×
×
Table A2.
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors×
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Table A2.
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors×
×
Table A3.
Multivariable Associations between Acute Kidney Injury and Risk Factors
Multivariable Associations between Acute Kidney Injury and Risk Factors×
Multivariable Associations between Acute Kidney Injury and Risk Factors
Table A3.
Multivariable Associations between Acute Kidney Injury and Risk Factors
Multivariable Associations between Acute Kidney Injury and Risk Factors×
×
Fig. 1.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
Fig. 1.
Flow chart. BP = blood pressure; EGFR = estimated glomerular filtration rate.
×
Fig. 2.
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Fig. 2.
Lowest mean arterial pressure (MAP) thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 3.
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
Fig. 3.
The lowest mean arterial pressure (MAP) thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and absolute and relative lowest MAP thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that there was a change point (i.e., decreases steeply up and then flattens) around 65 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 4.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Fig. 4.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for myocardial injury after noncardiac surgery (MINS). Univariable and multivariable relationship between MINS and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of MINS was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 5.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
Fig. 5.
Time-weighted average (TWA) mean arterial pressure (MAP) under absolute and relative thresholds for acute kidney injury (AKI). Univariable and multivariable relationship between AKI and TWA MAP under absolute and relative thresholds. (A) and (C) Estimated probability of AKI were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. (A) and (B) show that MAP less than 65 mmHg was a change point since the risk of AKI was starting to increase more compared to the thresholds of 70 and 75 mmHg, but 20% was not a change point from (C) and (D).
×
Fig. 6.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
Fig. 6.
Interaction between effects on myocardial injury after noncardiac surgery (MINS). (A) and (C) Estimated probability of MINS were from the univariable moving-window with the width of 10% data; (B) and (D) were from multivariable logistic regression smoothed by restricted cubic spline with three degrees and knots at 10th, 50th, and 90th percentiles of given exposure variable. Multivariable models adjusted for covariates in table 1. The interaction P values between the lowest mean arterial pressure (MAP) and baseline were < 0.001 and 0.84 between the lowest % MAP decrease and baseline, respectively. However, (A) and (B) plots show that there were no strong interaction effects as long as MAP is less than 65 mmHg.
×
Table 1.
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS×
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Table 1.
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS
Patient Baseline and Intraoperative Characteristics by Postoperative AKI and MINS×
×
Table 2.
Univariable Relationship between MAP Exposures and Outcomes
Univariable Relationship between MAP Exposures and Outcomes×
Univariable Relationship between MAP Exposures and Outcomes
Table 2.
Univariable Relationship between MAP Exposures and Outcomes
Univariable Relationship between MAP Exposures and Outcomes×
×
Table 3.
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*×
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Table 3.
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*
Interaction P Values between Baseline MAP and Postoperative AKI and MINS*×
×
Table 4.
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
MINS: Multivariable Association with Absolute and Relative MAP Thresholds×
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
Table 4.
MINS: Multivariable Association with Absolute and Relative MAP Thresholds
MINS: Multivariable Association with Absolute and Relative MAP Thresholds×
×
Table 5.
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds×
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
Table 5.
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds
AKI: Multivariable Associations with Absolute and Relative MAP Thresholds×
×
Table A1.
Summarized Statistics of MAP
Summarized Statistics of MAP×
Summarized Statistics of MAP
Table A1.
Summarized Statistics of MAP
Summarized Statistics of MAP×
×
Table A2.
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors×
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Table A2.
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors
Multivariable Associations between Myocardial Injury after Noncardiac Surgery and Risk Factors×
×
Table A3.
Multivariable Associations between Acute Kidney Injury and Risk Factors
Multivariable Associations between Acute Kidney Injury and Risk Factors×
Multivariable Associations between Acute Kidney Injury and Risk Factors
Table A3.
Multivariable Associations between Acute Kidney Injury and Risk Factors
Multivariable Associations between Acute Kidney Injury and Risk Factors×
×
Link ID: 2223787
  • Link Type: podcast-article
  • Linked Multimedia Creation Date: 12/12/2016 4:34:05 PM
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  • Multimedia Title: Relationship between intraop MAP and MINS or AKI
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