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Modifiable and Nonmodifiable Factors Associated With Perioperative Failure of Extraglottic Airway Devices

Vannucci, Andrea, MD, DEAA*; Rossi, Isabella T., MD; Prifti, Kevin, BS; Kallogjeri, Dorina, MD; Rangrass, Govind, MD; DeCresce, David, MD; Brenner, Daniel, MD, PhD§; Lakshman, Neel, BA*; Helsten, Daniel L., MD; Cavallone, Laura F., MD

doi: 10.1213/ANE.0000000000002659
Critical Care and Resuscitation: Original Clinical Research Report
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SDC

BACKGROUND: Extraglottic airway device (EGA) failure can be associated with severe complications and adverse patient outcomes. Prior research has identified patient- and procedure-related predictors of EGA failure. In this retrospective study, we assessed the incidence of perioperative EGA failure at our institution and identified modifiable factors associated with this complication that may be the target of preventative or mitigating interventions.

METHODS: We performed a 5-year retrospective analysis of adult general anesthesia cases managed with EGAs in a single academic center. Univariable and multivariable logistic regressions were used to identify clinically modifiable and nonmodifiable factors significantly associated with 3 different types of perioperative EGA failure: (1) “EGA placement failure,” (2) “EGA failure before procedure start,” and (3) “EGA failure after procedure start.”

RESULTS: A total of 19,693 cases involving an EGA were included in the analysis dataset. EGA failure occurred in 383 (1.9%) of the cases. EGA placement failure occurred in 222 (1.13%) of the cases. EGA failure before procedure start occurred in 76 (0.39%) of the cases. EGA failure after procedure start occurred in 85 (0.43%) of the cases. Factors significantly associated with each type of failure and controllable by the anesthesia team were as follows: (1) EGA placement failure: use of desflurane (odds ratio [OR], 1.67; 95% confidence interval [CI], 1.23–2.25) and EGA size 4 or 5 vs 2 or 3 (OR, 0.07; 95% CI, 0.05–0.10); (2) EGA failure before procedure start: use of desflurane (OR, 2.05; 95% CI, 1.23–3.40) and 3 or more placement attempts (OR, 4.69; 95% CI, 2.57–8.56); and (3) EGA failure after procedure start: 3 or more placement attempts (OR, 2.06; 95% CI, 1.02–4.16) and increasing anesthesia time (OR, 1.35; 95% CI, 1.17–1.55).

CONCLUSIONS: The overall incidence of EGA failure was 1.9%, and EGA placement failure was the most common type of failure. We also found that use of desflurane and use of smaller EGA sizes in adult patients were factors under the direct control of anesthesia clinicians associated with EGA failure. An increasing number of attempts at EGA placement was associated with later device failures. Our findings also confirm the association of EGA failure with previously identified patient- and procedure-related factors such as increased body mass index, male sex, and position other than supine.

From the *Department of Anesthesiology, University of Mississippi Medical Center, Jackson, Mississippi

Department of Anesthesiology, Washington University in St Louis, St Louis, Missouri

Department of Otolaryngology, Research Statistician at Barnes Jewish Hospital, St Louis, Missouri

§Department of Emergency Medicine, Johns Hopkins University, Baltimore, Maryland.

Published ahead of print December 15, 2017.

Accepted for publication September 29, 2017.

Funding: None.

The authors declare no conflicts of interest.

This study was entirely conducted at Barnes Jewish Hospital and the School of Medicine of Washington University in St Louis.

LMA Classic, LMA Unique, LMA Flexible, and LMA Fastrach are registered trademarks of Teleflex Incorporated or its affiliates.

Reprints will not be available from the authors.

Address correspondence to Andrea Vannucci, MD, DEAA, Department of Anesthesiology, University of Mississippi Medical Center-School of Medicine, 2500 N State St, Jackson, MS 39216. Address e-mail to avannucci@umc.edu.

KEY POINTS

  • Question: Are there modifiable risk factors that can decrease the chances of extraglottic airway device (EGA) failure in adult patients?
  • Findings: In this retrospective observational study, use of desflurane and use of EGA sizes 2 and 3 were associated with increased odds ratios of EGA failure.
  • Meaning: In adult patients, avoidance of desflurane and of smaller EGA sizes may be associated with reduced EGA failure rates.

Extraglottic airway devices (EGAs) are frequently used as an alternative to tracheal intubation but may result in potentially severe complications such as aspiration, laryngospasm, and negative pressure pulmonary edema.1–5 EGAs can fail because of improper placement, dislodgement, airway obstruction, or regurgitation of gastric contents. Failure to properly place an EGA has traditionally been attributed to inadequate technique, insufficient depth of anesthesia, or supraglottic anatomical factors such as limited mouth opening, palatinus torus, and enlarged tonsils.1,6–9

Recent large retrospective analyses in adult and pediatric patients have examined the incidence of factors associated with EGA failure.3,5,10 Independent predictors for EGA failure in adults included surgical table rotation, male sex, poor dentition, and increased body mass index (BMI); in children: ear/nose/throat surgical procedures, non-outpatient admission status, prolonged surgical duration, congenital/acquired airway abnormalities, age <5 years old, body weight <16 kg, device sizes 1 and 1.5, patient transport, and lateral position. While these predictors are directly related to either patient- or procedure-related characteristics and therefore helpful in risk stratification, they are less useful in guiding anesthetic management once clinicians have made the decision to use an EGA.

Figure

Figure

Several small prospective studies have suggested that factors controllable by the anesthesia team, such as depth of anesthesia, choice of inhalational agent, and ventilation mode, may also play a critical role in EGA failure in routine clinical practice.10–12 However, these results have not been reproduced in large observational studies where patient-, procedure-, and anesthesia-related predictors interact and may influence outcomes. We therefore designed this retrospective study to assess whether we could identify factors associated with EGA failure that are controllable by the anesthesia team as a preliminary step to design preventative or mitigating strategies. We further hypothesized that specific independent predictors could be identified for each of 3 types of perioperative EGA failure (Figure): “EGA placement failure” (failure 1), “EGA failure before procedure start” (failure 2), and “EGA failure after procedure start” (failure 3).

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METHODS

This article adheres to the applicable Equator guidelines and conforms to the journal’s requirements for human and animal trials.13 The institutional review board of Washington University in St Louis approved this retrospective observational study. Funding was provided by a Washington University School of Medicine Faculty Practice Plan Patient Safety and Quality Improvement Research Grant (Grant ID: 8014–88). A written informed consent was waived by the Institutional Review Board as this retrospective study presented minimal risk to patients and measures to prevent Health Insurance Portability and Accountability Act violations were implemented in accordance with institutional practices.

The setting of the study was a large US academic teaching institution where elective and emergent cases of all surgical specialties are performed. All adult cases where an EGA was documented as the used or intended airway device during a procedure requiring general anesthesia between January 2010 and December 2014 were included in the analysis. This time period was chosen because it immediately followed the adoption of an anesthetic electronic record across all locations staffed by our department.

Based on an estimated 3500 and 4000 cases annually performed at our institution with an EGA as the primary intended airway device, and on EGA failure rates reported in the literature (1.1%−5%), we calculated that we could expect at least 17,500 EGA cases and 180 outcomes of interest (failures). This sample size would allow us to include up to 20 variables in our multivariate model based on the rule of requiring 8–10 cases with the condition of interest for every variable in the model.

Exclusion criteria were patients <18 years old or those undergoing ear/nose/throat, interventional pulmonology, or cardiothoracic procedures to avoid possible surgery-related confounders directly affecting the airway or respiratory system that could by themselves determine the need for airway device exchanges or cause airway complications.

Probable cases of interest were identified by querying the archived anesthesia electronic records from January 1, 2010, to December 31, 2014. The electronic anesthesia record used during the study period was MetaVision (iMDsoft, Dedham, MA). Data collection included preoperative, intraoperative, and immediate postoperative information (including medical record number and other administrative case identifiers, patient comorbidities, date of surgery, staff assigned to the case, anesthetic start and end times, anesthetic and surgical procedures, position of the patient, type and size of airway devices, administered drugs, and ventilation modalities) as documented by clinicians in the Department of Anesthesiology at Washington University in St Louis. When needed because of incomplete documentation on the anesthetic record, demographic, anthropometric, and other clinical data were extracted from BJC ClinDesk (BJH Healthcare, St Louis, MO), a separate electronic medical record in use at the medical center. We obtained the final postoperative disposition—after postanesthesia care unit discharge—from the administrative records of the hospital.

During the study period, EGA types regularly used at our institution included the following: LMA® Classic™ (Teleflex Medical Europe, Ltd, Co, Westmeath, Ireland), LMA® Unique™ (Teleflex Medical Europe, Ltd, Co, Westmeath, Ireland), LMA® Flexible™ (Teleflex Medical Europe, Ltd, Co, Westmeath, Ireland), Igel (Intersurgical, Inc, East Syracuse, NY), and LMA® Fastrach™ (Teleflex Medical Europe, Ltd, Co, Westmeath, Ireland). In our analysis, we included several cases where the LMA® Fastrach™ was used as a “regular LMA” but not those where the Fastrach was used as a tool to facilitate tracheal intubation. For the purpose of the analysis, we categorized these devices as either a first- or second-generation EGA, with the second-generation EGA having the presence of a channel for the advancement of a gastric tube as suggested by Cook.14

Perioperative EGA failures were defined a priori and classified into 3 groups as follows: (1) failure 1: the immediately recognized inability to correctly position the EGA resulting in an alternative approach needed to control the airway before proceeding with surgery; (2) failure 2: the unanticipated need to reposition, remove, or replace a previously satisfactory EGA with another EGA or airway device to restore airway patency, ventilation, or airway protection before the surgical start time; and (3) failure 3: the unanticipated need to reposition, remove, or replace a previously satisfactory EGA with another EGA or airway device to restore airway patency, ventilation, or airway protection at or after the surgical start time.

Probable cases of EGA failure were found by querying the archived anesthesia electronic records to identify the following: (1) cases reporting EGA insertion failure in the electronic anesthetic record (at our center, the field “attempted airway success” with binary outcome “yes/no” is a built-in function of the electronic record configuration); (2) cases in which both an EGA and endotracheal tube were used during the same procedure suggesting a possible unplanned airway exchange; (3) cases in which the clinicians checked “no” in the field for “EGA attempted failure,” but the use of a neuromuscular blocking agent was documented; and (4) free-text comments, including the terms “LMA,” “Igel,” “laryngeal,” or “mask,” suggesting a possible EGA failure event.

After removal of duplicate cases, manual chart review allowed further data collection, including the timing and type of EGA failure, and removal of cases where EGAs were used as a rescue device (those in which laryngoscopy was performed before EGA placement) and those in which the EGA was converted to an endotracheal tube due to a change in surgical plans.

“Anesthesia start,” “anesthesia end,” and “surgery start” times were obtained from the electronic anesthetic record. “Time of anesthesia induction” was either documented by the clinicians on the electronic record or recognized as the first bolus of an induction agent when the induction time was not documented. When the information could vary throughout the procedure (such as patient position and ventilation mode), the first-documented level was used for analysis.

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Statistical Analysis

Data quality was assessed using electronic and manual data validation strategies developed by the departmental division of outcome research. The prevalence of each type of failure was calculated as the number of cases with each type of failure over the total number of EGA cases. Frequency and relative frequency were used for the description of the categorical-level characteristics. Mean and standard deviation were used for continuous-level characteristics that were normally distributed.

From the 19,693 surgical cases in our dataset, 13,991 patients had only 1 surgery, and 2270 patients had >1 surgery. We tested the independence of observations through a generalized estimating equation approach, and since that assumption was valid, we elected to perform logistic regression analysis.

Logistic regression analysis was used to investigate the association of patient characteristics and clinical factors under the control of the anesthesia clinicians associated with each type of EGA failure. We started our forward stepwise logistic regression with variables identified as significantly associated with each type of failure in the univariable analysis. An α level of .05 set the criteria for variables to enter and stay in the model. Multicollinearity between variables included in multivariable analysis was assessed using the variance inflation factor.15

All variables included in final models had a variance inflation factor <2, suggesting that multicollinearity was not an issue. Adjusted odds ratios (ORs) and 95% confidence interval (CI) were used to report the results of the final model resulting from forward stepwise multivariable logistic regression. All statistical tests were 2 sided and evaluated at the α level of .05. SAS 9.4 (SAS Institute, Inc, Cary, NC) was used for statistical analysis of the data.

The concordance statistic, also known as the C-statistic, was used to assess the discriminative ability of a logistic regression model. The C-statistic is equivalent to the area under the receiver operating characteristic curve, with 0.5 being the null value.16

Manual chart review was used to complete missing data, wherever possible. We did not perform imputation for missing data.

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RESULTS

A total of 19,693 cases using an EGA to maintain airway patency and facilitate ventilation during general anesthesia were identified and included in the analysis. One hundred twelve of the cases were performed using primarily total intravenous (IV) anesthesia. After electronic and manual review, the cumulative prevalence of the 3 types of EGA failure was 1.9% (n = 383 cases). Failure 1 occurred in 222 of 19,693 cases (1.13%), failure 2 occurred in 76 of 19,693 cases (0.39%), and failure 3 occurred in 85 of 19,693 cases (0.43%).

Of the 2270 patients who underwent >1 surgery during the study period, 4 individuals had 2 episodes of failure on separate dates. All of these 4 patients had 1 episode of failure 1 and, respectively, a second episode of failure 2, failure 1, failure 2, and failure 3.

Distribution of patient characteristics and details of the anesthesia technique and of the surgical procedures in patients with and without EGA failure are reported and compared in Tables 1 and 2.

Table 1

Table 1

The median time interval between induction of anesthesia and failure of the EGA before procedure start was 8 minutes, with an interquartile (IQ) range of 11 minutes. The median time interval between procedure start and EGA failure after the start of the procedure was 19 minutes, with an IQ range of 30 minutes. The median time interval between induction of anesthesia and EGA failure after the start of the procedure was 33 minutes, with an IQ range of 28 minutes.

Patients who had EGA failure received higher average doses of propofol (2.29 mg/kg of body weight in patients with no EGA failure versus 2.99 mg/kg in patients with failure 1, 3.23 mg/kg in patients with failure 2, and 3.62 mg/kg in patients with failure 3). Fentanyl was given in 70% of cases without EGA failure compared to 63% of failure 1, 68% of failure 2, and 61% of failure 3 cases, compared to 63% of failure 1, 68% of failure 2, and 61% of failure 3 cases. The percentages of patients receiving midazolam were, respectively, 85% of the group who did not have failure, 75% of failure 1, 81% of failure 2, and 76% of failure 3.

Depolarizing neuromuscular blocking agents were used in 1% (n = 186) of the patients with no EGA failure and more frequently in patients with EGA failure: 42% in the failure 1 group (95% CI, 36%–49%), 50% in the failure 2 group (95% CI, 39%–62%), and 35% in the failure 3 group (95% CI, 25%–46%). Nondepolarizing neuromuscular blocking agents were used in 0.1% of cases with no EGA failure, 2.3% (95% CI, 0.2%–4%) of cases with failure 1, and never used in failure 2 or failure 3.

The use of spontaneous ventilation was associated with a nonsignificant trend toward lower incidence of failures that occurred after EGA placement. ORs (95% CI) were, respectively, 0.63 (0.30–1.30) for failure 2 and 0.77 (0.22–2.8) for failure 3.

On the contrary, volume-controlled ventilation was the ventilator setting most strongly associated with post-placement EGA failures. ORs (95% CI) were, respectively, 10.62 (4.52–24.95) for failure 2 and 8.61 (2.38–31.15) for failure 3.

The OR of each type of failure was not different in cases using second-generation EGAs as compared to first-generation EGAs. Similarly, use of an EGA with a size outside of the recommended body weight by the manufacturer was not associated with EGA failure (Table 2).

Table 2

Table 2

Variables identified through univariable logistic regression as associated with failure 1 were incorporated into a forward stepwise multivariable model and included age, sex, American Society of Anesthesiologists (ASA) category, Mallampati class, chronic obstructive pulmonary disease, congestive heart failure, use of desflurane, EGA size, use of nitrous oxide, cases performed after hours, surgical unit, and intraoperative use of norepinephrine. The final multivariable model included age, sex, use of desflurane, EGA size (2 and 3 vs 4 and 5), and the surgical units where the procedures were performed (Table 3) and had a C-statistic of 0.85 (95% CI, 0.82–0.87).

Table 3

Table 3

Variables identified through univariable logistic regression as associated with failure 2 incorporated in a forward stepwise multivariable model and included BMI, ASA category, Mallampati class, use of desflurane, use of sevoflurane, number of airway attempts, patient position, and the surgical unit. The final multivariable model included BMI, use of desflurane, number of airway attempts, position, and surgical units (Table 4) and had a C-statistic of 0.78 (95% CI, 0.74–0.83).

Table 4

Table 4

Table 5

Table 5

Variables identified through univariable logistic regression as significantly associated with failure 3 were incorporated in a forward stepwise multivariable model and included BMI, male sex, ASA emergent procedure, Mallampati class, history of tobacco use, diabetes, CHF, obstructive sleep apnea, use of desflurane, number of airway attempts, length of anesthesia time, position, surgical unit, and use of resuscitation drugs during the case. The final multivariable model included only BMI, gender, ASA emergent procedure, history of congestive heart failure, and anesthesia time (Table 5) and had a C-statistic of 0.73 (95% CI, 0.69–0.78).

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DISCUSSION

In this retrospective, single-center study, we observed a cumulative incidence of EGA failure of 1.9%, a value similar to prior studies.3,5 Although relatively rare, EGA failure still appears as a relevant event for clinicians to address considering how widespread the use of these devices is and the possibility that preventing episodes of EGA failure may lead to improved patient outcomes.2,15 Our results support the initial hypotheses that EGA failure is associated with risk factors controllable by the anesthesia team and that each of the 3 types of EGA failure is associated with specific predictors.

EGA failure was an overall “early event” during the surgical procedure. Lower rates of EGA failure were detected in the anesthesia unit that placed the highest number of EGAs, which suggests that failures may be related to the experience of the provider or the type of surgical procedures that are prevalent in those areas (Table 2). Unfortunately, our results are unable to answer this question.

We also assessed whether the incidence of EGA failure would be lower with the use of a second-generation device due to an outlet for gastric decompression. Interestingly, we did not find a difference in the failure rate of first-generation compared to second-generation EGAs possibly because the latter were used in patients at higher risk of complications that may have otherwise resulted in failure with a first-generation EGA. Unfortunately, our data are unable to test this hypothesis.

We found that failure 1 (placement failure) was the most common type of EGA failure, with an incidence more than the combined incidences of failure 2 and failure 3. Similar to prior studies, we also observed that using an EGA size different from that based on weight and recommended by the manufacturer was not associated with increased failure rates even though the use of an EGA of smaller size (2 and 3) in adult patients was associated with an increased rate of placement failure (Tables 2 and 3).5

The findings that failure 1 was the most common type of failure and multiple placement attempts were associated with failure 2 and failure 3 underscore the importance of being familiar with the physical characteristics of available airway devices, mechanisms of the most common types of malpositioning, and troubleshooting strategies as recently proposed by Van Zundert et al.16,17 Notably, while the Mallampati score was predictive of all types of EGA failure in univariable analysis, it was not a predictor in the multivariable model. This result conflicts with a previous study and suggests that predictors of failure 1 may not be easy to identify with a standard preoperative airway examination.18

We found that the only 2 modifiable predictors of failure 1 were use of desflurane and EGA size. However, we also found that nonmodifiable factors such as age and male sex predicted EGA failure. Male sex has previously been associated with EGA failure in a large study4 but was not shown to be a valid predictor in a smaller population.19 Our results, again in a large population, support the hypothesis that EGA failure may be more frequent in males, as proposed by Ramachandran et al.4

In our analyses, desflurane was associated with both failure 1 and failure 2 modes. One possible explanation for this finding is that desflurane heightens airway reactivity,20,21 and use of desflurane before securing the airway and immediately after EGA placement may have increased reactivity to the EGA positioning. Such an effect may be particularly important during phases of anesthesia when the anesthetic depth may not be adequate to compensate for the intensity of stimulation. The association between use of desflurane and EGA failure is an interesting new result that differs from what was previously reported in a reasonably sized meta-analysis on this topic.10

Similar to previous studies,5 BMI was not a risk factor for failure 1 but was associated with an increase of the other 2 types of EGA failure (failure 2 and failure 3). This result suggests that the EGAs may have efficacy as a temporary rescue device during difficult airway management in obese patients. However, our results also suggest that the increased risk of EGA failure in obese patients should be considered when choosing to use EGAs in this patient population.

Other independent factors for failure 2 included multiple placement attempts, non-supine position, and increasing BMI. Based on the association with the covariate “3 or more placement attempts,” we hypothesize that this study group may have included some cases in which a form of malpositioning of the EGA was not immediately diagnosed by the clinicians but later became evident during patient positioning or on initiation of ventilator support.19

Failure 3 was associated with an increased BMI, male sex, ASA emergent cases, history of congestive heart failure, and increased anesthetic duration. Of note, the presence of emergent cases and increased anesthesia time among independent predictors in our study suggests that EGAs may be a suboptimal choice for emergent and/or longer lasting procedures.

Our retrospective study has limitations. Because our study involved retrospective data review, it is possible that we failed to capture all EGA failures. The real incidence of EGA failure may thus be higher than the figures we report. Notwithstanding this limitation, we feel that our approach allowed us to reproducibly identify factors associated with EGA failure across a large cohort of patients.

Another potential limitation of the study is intrinsic to the choice of using a stepwise approach as a variable selection method in building multivariable models. While we carefully included in the model(s) only variables that we considered clinically related to each of the failure types, it is possible that some of the variables found significant in our models may be overstated with this approach and may be specific to the chosen selection method.22

A few possible problematic decisions regarding the parameters included in the final statistical models were made. For example, we excluded the administration and doses of IV opioids, IV induction agents, and neuromuscular blocking drugs from the analysis as we felt that these drugs may have been given in response to EGA failure to deepen anesthesia and thus may not have been causative factors. In addition, we could not identify the exact time of administration or the sequence of drugs used in a reliable way from the anesthetic records as these factors are manually inputted by clinicians and are thus often approximated and imprecise.

Similarly, we excluded the parameter “ventilation mode” from the multivariable analysis because clinicians may often choose to use controlled ventilation to “rescue” an inadequately placed EGA that may not allow sufficient airflow to permit spontaneous or less invasive ventilation modes.

In contrast, our data on inhalational agent concentrations are likely accurate as they are automatically transferred from the anesthesia machine into the electronic record. We thus considered them as clinically valid factors to be tested in the multivariable models for failure 1 and failure 2.

An additional clinical limitation in this study was that the anesthetic management in this patient population was primarily inhalational anesthesia. Our findings may thus not translate to cases using total IV anesthesia.

Furthermore, although we could identify EGAs with and without gastric suction ports, the information regarding the specific EGA model was not always reported in the electronic record. As a result, we classified the different devices used in our study (Table 2) as either first- or second-generation EGA to allow for a meaningful statistical comparison. This variable was not significant in univariable analysis and was not entered in any of the multivariable models.

Despite these limitations, we believe that our study sheds light on factors affecting the use and failure of EGAs in “real-world” conditions. We found that EGA placement failure is the most common type of failure, and each of the 3 different types of failure is associated with specific factors.

In addition, our data suggest that “modifiable variables” under the control of the anesthesia team (such as the choice of inhalational agent, size of the EGA, and increased number of placement attempts) may play a role in EGA failure. Further research is warranted to clarify whether limiting the use of desflurane, decreasing the number of placement attempts, and possibly avoiding smaller size devices may reduce EGA failure in adult patients undergoing general anesthesia with EGAs.

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ACKNOWLEDGMENTS

The authors wish to recognize the outstanding support and assistance they have received from colleagues of the Division of Clinical and Translation Research of the Department of Anesthesiology at Washington University in St Louis in securing and managing the funds to conduct the study, assisting with Institutional Review Board approval, and ensuring compliance with institutional research policies.

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DISCLOSURES

Name: Andrea Vannucci, MD, DEAA.

Contribution: This author helped provide a substantial contribution to the conception and design of the work as well as assisted with data interpretation, and drafting and approving the manuscript.

Name: Isabella T. Rossi, MD.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: Kevin Prifti, BS.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: Dorina Kallogjeri, MD.

Contribution: This author helped design the statistical analyses for the study, assisted with data management, performed data analysis, assisted with data interpretation, and drafted and approved the manuscript.

Name: Govind Rangrass, MD.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: David DeCresce, MD.

Contribution: This author helped provide a substantial contribution to the conception and design of the work as well as assisted with data interpretation, and drafting and approving the manuscript.

Name: Daniel Brenner, MD, PhD.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: Neel Lakshman, BA.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: Daniel L. Helsten, MD.

Contribution: This author helped provide a substantial contribution to the data acquisition and data interpretation, and drafting and approving the manuscript.

Name: Laura F. Cavallone, MD.

Contribution: This author helped provide a substantial contribution to the conception and design of the work as well as assisted with data interpretation, and drafting and approving the manuscript.

This manuscript was handled by: Avery Tung, MD, FCCM.

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