Adjuvants to Mechanical Ventilation for Acute Respiratory ... · ii Adjuvants to Mechanical Ventilation for Acute Respiratory Failure Laveena Munshi Masters of Science Institute of

Adjuvants to Mechanical Ventilation for Acute Respiratory

Failure

by

Laveena Munshi

A thesis submitted in conformity with the requirements

for the degree of Masters of Science

Institute of Health Policy, Management and Evaluation

University of Toronto

© Copyright by Laveena Munshi 2016

ii

Adjuvants to Mechanical Ventilation for Acute Respiratory Failure

Laveena Munshi

Masters of Science

Institute of Health Policy, Management and Evaluation

University of Toronto

2016

Abstract

OBJECTIVES: To evaluate use of adjuvants to mechanical ventilation for acute respiratory

failure (ARF;2008-2013) and the impact of landmark publications on adoption and de-adoption.

METHODS: Adult patients with ARF who underwent mechanical ventilation were evaluated

using a large US quality improvement database. Adjuvant use was identified using International

Classification of Disease, 9th

Edition codes and billing data.

RESULTS: Among 514,913 ARF patients, 11,567 (2.3%) were treated with adjuvants. There

was an increase in recent years of extracorporeal membrane oxygenation and inhaled

epoprostenol but no change in inhaled nitric oxide or continuous paralysis over time. Segmented

regression analysis used to evaluate whether clinical practice was in accordance with evidence

from landmark studies, did not reveal any change in use following publication with the exception

of inhaled epoprostenol.

CONCLUSIONS: The use of adjuvants is infrequent across our population. Published evidence

to support current adoption/de-adoption appear to have had limited effect on practice.

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Acknowledgments

I would like to acknowledge the support and guidance I received from my thesis committee Drs.

Gordon Rubenfeld (supervisor) Eddy Fan, Hannah Wunsch, Niall Ferguson and Therese Stukel.

Their patience, wisdom and mentorship have had a great impact on the career path I hope to

pursue.

I would also like to acknowledge Dr. Hayley Gershengorn for her contribution in assisting with

the database and for facilitating access to the data in order for me to perform the data analysis at

Montefiore Medical Center.

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Table of Contents

Contents

Acknowledgments.......................................................................................................................... iii

Table of Contents .......................................................................................................................... iiv

List of Tables ................................................................................................................................. vi

List of Figures .............................................................................................................................. vii

List of Appendices ...................................................................................................................... viii

Chapter 1 Adjuvants to Mechanical Ventilation for Acute Respiratory Failure ...............................

Background .................................................................................................................................1 1.

1.1 Rationale, Evidence and Current Use of Adjuvant Therapy

1.1.1 Acute Respiratory Failure Management……………………………………………1

1.1.2 Pharmacologic Adjuvants………………………………………………………..…2

1.1.3 Non-Pharmacologic Adjuvants…………………………………………………..…5

1.1.4. Factors Affecting Adoption and De-adoption……………………………………...7

1.1.5. Conclusions………………………………………………………………………....9

2. Adjuvant Therapy to Mechanical Ventilation Changes in Use and Factors Associated with

Use………………………………………………………………………………………………10

2.1 Introduction………………………………………………………………………………10

2.2 Methods…………………………………………………………………………………..11

2.2.1 Study Population…………………………………………………………………..11

2.2.2 Outcomes…………………………………………………………………………12

2.2.3 Statistical Analysis……………………………………………………………….12.

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2.2.4 Sensitivity Analysis……………………………………………………………….14

2.3 Results……………………………………………………………………………………15

2.3.1 Cohort Assembly…………………………………………………………………..15

2.3.2 Changes Over Time………………………………………………………………..16

2.3.3 Factors Associated with Use……………………………………………………….18

2.4 Discussion………………………………………………………………………………..19

3. Conclusions and Future Direction…………………………………………………………....20

References……………………………………………………………………………………44

Appendix……………………………………………………………………………….…….48

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List of Tables

Table 1: Reported Use for Common Adjuvants in Acute Respiratory Failure

Table 2: ICD9-CM Inclusion and Exclusion Criteria Codes

Table 3: Landmark Studies Evaluated

Table 4: Baseline Demographic Characteristics

Table 5: Adjuvant Frequencies

Table 6: Patient and Hospital Characteristics According to Adjuvant

Table 7: Sensitivity Analyses

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List of Figures

Figure 1. Adjuvants for Acute Respiratory Failure

Figure 2: Factors that Drive Decision Making

Figure 3: Cohort Creation

Figure 4: Changes in Use of Adjuvant Therapy

Figure 5: Impact of Landmark Publications on Changes in Use Over Time

Figure 6: Changes in Use of Pulmonary Artery Catheter

Figure 7: Factors Associated with Adjuvant Use

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List of Appendices

Table 1: Neuromuscular Blockading Agent Dose Determination

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Adjuvants to Mechanical Ventilation for Acute Respiratory

Failure

Background 1

1.1 Rationale, Evidence and Current Use of Adjuvant Therapy

1.1.1 Acute Respiratory Failure Management

Acute respiratory failure (ARF) is a common reason for admission to an intensive care unit

(ICU) and the need for mechanical ventilation. Acute respiratory distress syndrome (ARDS) is a

severe form of hypoxemic ARF, with bilateral infiltrates consistent with pulmonary edema on

chest radiography that is not primarily due to a cardiogenic etiology (1). Mortality from ARF

and ARDS is high and similar across both categories (30-40%) with most deaths resulting from

multi-organ failure and sepsis (2). Limited pharmacologic therapy has proven effective in ARF

and management is focused primarily on supportive care with mechanical ventilation (1, 3-5).

Currently, lung protective pressure- and volume-limited ventilatory strategies aimed at

mitigating ventilator-associated lung injury (VALI) have become the standard of care (5).

Despite the use of lung protective ventilation, a number of patients may develop refractory

hypoxemia and/or hypercapnia, and may not be able to achieve adequate gas exchange without

using injurious levels of ventilatory support.

An adjuvant for ARF is any intervention, in addition to or instead of mechanical ventilation, that

is used to facilitate gas exchange or enhance compliance with lung protective ventilation (Figure

1). Pharmacologic adjuvants have been the focus of many studies for years and include diuretics,

corticosteroids, neuromuscular blocking agents and inhaled pulmonary vasodilators. Non-

pharmacologic agents include prone positioning, high frequency oscillatory ventilation and

extracorporeal life support. These non-pharmacologic options have been the focus of many large

trials in recent years (Table 1). A series of proposal algorithms for adjuvant application have

been proposed over recent years (Figure 1). While most of the evidence surrounding adjuvant

use has focused on patients with ARDS, recent international observational data has demonstrated

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the application of adjuvants in patients with ARF even if formal criteria for ARDS is not met or

in patients in whom ARDS is unrecognized (3).

1.1.2 Pharmacologic Adjuvants

Neuromuscular blocking agents may minimize ventilator associated lung injury by preventing

large spontaneous tidal volumes, reducing ventilator dys-synchrony, and possibly decreasing the

inflammatory response associated with ARF and ARDS (6). In addition, paralysis may stop any

subclinical evidence of muscle activity, potentially improving oxygenation through minimization

of oxygen consumption. A large retrospective observational study of data from 2004-2006,

evaluated the frequency of use and impact of early administration of paralysis in patients with

severe sepsis who were mechanically ventilated and found that 23% of patients received early

paralysis (7). Early paralysis was associated with a lower mortality (32% vs. 38%) In a

randomized controlled trial (RCT) in 2010, the continuous, early administration of cisatracurium

in moderate-severe ARDS (PaO2/FiO2 <150) was associated with an improvement in 90-day

mortality (8). The trial found that the beneficial effect of cisatracurium was confined to patients

presenting with a PaO2/FiO2 < 120 suggesting that patients with severe ARDS might receive the

greatest benefit from this intervention. Following this publication, only 15% of UK physicians

report using neuromuscular blocking agents ―routinely‖ (9). Most recently, in the Large

Observational Study to Understand the Global Impact of Severe ARF (LUNG-SAFE) study, a

prospective observational study of ARF and ARDS across 50 countries, paralysis was used in

22% of all ARDS patients and in 38% of the severe ARDS subgroup (3).

Non-hydrostatic pulmonary edema is one of the hallmarks of ARDS and can complicate all

causes of ARF. Additionally, excess fluid administered during the resuscitation phase of septic

shock could contribute to the development of abdominal compartment syndrome, further

restricting lung expansion. The role of a conservative fluid management strategy combined with

diuretic administration during ARF management has been evaluated as a mechanism by which

one could improve lung compliance and oxygenation and has been demonstrated to reduce

duration of mechanical ventilation. The Fluid and Catheter Treatment Trial (FACTT) assessed a

conservative fluid management strategy combined with diuretic administration as a mechanism

to improve lung compliance and oxygenation, finding an increased number of ventilator free

days (10). However, the complex algorithm, lack of mortality benefit and possible risk of

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neurocognitive complications might impact widespread adoption (11). Evidence of adoption of

diuretic administration has not been extensively evaluated following this publication. Variability

in use of diuretics for ARDS has been reported across different centers. In a recent survey

administered to intensivists in Australia and New Zealand evaluating diuretic use, 74% of

intensivists indicated that they would administer loop diuretics for ARDS; however,

approximately 20% reported that they would not (12). An observational study evaluating

prescribing patterns across 150 ARDS patients demonstrated that loop diuretics were only

actually prescribed in 39% of patients (13). Despite an increasing focus on the harms associated

with a positive fluid balance in patients, there is a lack of evidence on how physicians implement

this in practice. Non-invasive hemodynamic monitoring devices leading potentially to more

precise evaluations of volume status or a focus on ―de-resuscitation‖ in sepsis has perhaps led to

changes in diuretic administration. More insight into current practice, particularly in light of the

recent publication of ―FACTT lite‖ which provides a simpler approach to a conservative fluid

management strategy, is needed to highlight whether areas for improved compliance with

diuresis exist (14).

The early administration of corticosteroids as a mechanism to combat septic shock in order to

down regulate the systemic inflammation as well as the late administration of steroids in the

fibroproliferative phase of ARDS, has been evaluated in a number of clinical trials (15, 16).

However, beyond steroid-responsive precipitants for ARDS (e.g. systemic vasculitis), a role for

corticosteroids in routine care of ARDS patients has not been established. Promising preliminary

evidence currently exists for its potential role with ARF in order to prevent ARDS in the setting

of severe community acquired pneumonia (17). Despite these findings, current use of

corticosteroid for ARDS patients remains variable but high. One study reports use in 41% of

ARDS cases – higher than the use of diuretics or neuromuscular blocking agents (13). In a 2010

questionnaire in German ICUs regarding ARDS management practices, corticosteroids were

used in 52% of hospitals (18). In a separate study, 70% of UK physicians surveyed in 2012

endorsed the use of corticosteroids; however, only 6% used them routinely (9). The LUNG-

SAFE study found that high dose corticosteroids (equivalent to >1mg/kg methylprednisone) was

used in 17.9% of patients with ARDS and 23.3% in the subset with severe ARDS (3).

Inhaled nitric oxide (NO) is a selective pulmonary vasodilator, which acts by preferentially

diffusing to capillary beds of less inflamed alveoli leading to a reduction in ventilation/perfusion

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mismatch and pulmonary vascular pressures in addition to having anti-inflammatory properties

(19). The use of inhaled nitric oxide as a rescue therapy was characterized across 6 ARDS

Network trials between 1996-2006 (20). Of the patients who received rescue therapy, inhaled

nitric oxide was the second most commonly employed agent during that time period (28% of

patients receiving rescue therapies). The most recent meta-analyses of ARDS patients has since

demonstrated no mortality benefit associated with NO use regardless of severity (21). Moreover,

the use of NO was associated with an increase in the incidence of renal failure(22). In surveys,

29-44% of intensivists’ from the UK and Germany report administering NO in ARDS (9, 18). In

the LUNG-SAFE study, the frequency of use of any type of inhaled vasodilator was found to be

much lower: 7.7% in all ARDS and 13.0% in the severe ARDS subgroup (3). However, the

impact of this more recent evidence from the 2014 meta-analysis on frequency of use of NO has

not been described.

1.1.3 Non-Pharmacologic Agents

Theoretically, prone positioning may prevent lung injury by recruiting non-dependent lung,

improving respiratory mechanics and clearing pulmonary secretions. The creation of more

homogeneous chest wall compliance, offloading the weight of the heart and minimizing the

weight of the abdominal contents on the diaphragm are mechanisms by which prone positioning

may enhance respiratory mechanics and lead to an increase in recruitable lung units (4, 23). Prior

to 2013, studies applied prone positioning to patients with a range of severity of ARDS. While

these trials consistently demonstrated an improvement in oxygenation with prone positioning, a

reduction in mortality was only seen in post hoc subgroup analyses of the most severe ARDS

cohorts (24). In 2010, 60% of German centers reported that they proned ARDS patients and 84%

of surveyed UK intensivists in 2012 reported that they would employ prone positioning as a

rescue strategy (9, 18). An RCT in 2013, which focused on patients with moderate/severe ARDS

(PaO2/FiO2 <150), demonstrated an absolute mortality risk reduction of 17% with prolonged

intermittent prone positioning (25). Since this trial; however, the LUNG-SAFE study revealed

relatively low rates of proning: 7.9% of all ARDS (and 16.3% of severe ARDS patients) (3).

High frequency oscillatory ventilation (HFOV) is an open lung ventilatory strategy that attempts

to recruit the lung using a high mean airway pressure and minimizes cyclic tidal reopening and

closing. Although early randomized-controlled trials of HFOV in adults suggested the possibility

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of benefit (26), two recent, high quality, large-scale trials failed to show any mortality benefit

and one trial suggested possible harm when employed in moderate to severe ARDS (27, 28). One

possible explanation of the lack of benefit was more hemodynamic instability in the HFOV arm,

possibly attributable to a decrease in venous return, or impairment of right ventricular afterload

with higher mean airway pressure. Occult barotrauma and an increase in sedative requirements

are additional plausible mechanisms (27). Frequency of use as a rescue strategy ranged from 7%-

50% in earlier literature (9, 20). Most recently, much lower use has been reported from LUNG-

SAFE (1.2% across all ARDS and 1.5% in the severe ARDS subgroup) (3).

Venovenous extracorporeal membrane oxygenation (ECMO) is a form of partial

cardiopulmonary bypass that acts as an oxygenating and ventilatory shunt and can allow a

reduction in the intensity of invasive mechanical ventilation or complete lung rest. An RCT in

2009, the Conventional Ventilator Support vs. Extracorporeal Membrane Oxygenation for

Severe Adult Respiratory Failure (CESAR) trial, evaluated the impact of transport to an ECMO

capable center in patients with severe ARDS and demonstrated an improvement in disability-free

survival (29). However, some unanswered questions included whether the improved outcome

was due to ECMO itself or being managed at an expert center, as not all patients received

ECMO. In addition, the lack of compliance with lung protective ventilation in the non-

protocolized control arm might have contributed to the difference in outcomes (29). Given some

conflicting recent evidence regarding its benefit in severe ARDS (30), an international multi-

center trial is currently underway to evaluate its use for severe ARDS patients (NCT01470703).

The creation of modern extracorporeal circuitry technology in combination with the publication

of the CESAR trial and the subsequent H1N1 influenza outbreak has led to an exponential

increase in use of ECMO; according to the Extracorporeal Life Support Organization: 117 cases

of adult respiratory ECMO reported in 2004 to 1,497 cases reported in 2014 (31). In the LUNG-

SAFE study, 6.6% of patients with severe ARDS across the 50 countries received ECMO (3).

The adjuvants reviewed here are only a few of many potential pharmacologic (e.g. aspirin,

statins) and non-pharmacologic (e.g. non-invasive ventilation) adjuvants that continue to be

assessed.

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1.1.4 Factors affecting adoption and de-adoption

Despite many intervention studies with no difference in outcomes and given the heterogeneity of

patients with ARF, decision making about the use of adjuvant therapy in specific subgroups of

patients, is complex. For example, in advance of the positive proning trial described above,

many clinicians advocated for the use of prone ventilation based on the compelling physiologic

rationale, subgroup evidence of benefit for severe ARDS and limitations of the existing trials

(24). Since statistically negative trials may not be able to prove lack of efficacy in specific

subgroups, arguments can be offered about the use of treatments from these trials in different

patient subsets or with different protocols than those studied. Information gained from subgroup

analyses or further insight on adjuvant administration has led to new trials re-evaluating their

use.

However, despite this, trial results will continue to remain only one component of medical

decision-making. Factors that impact adoption or de-adoption often extend beyond evidence.

More importantly, when the evidence base is weak or inconsistent, as it is in much of medicine,

factors other than evidence drive adoption and de-adoption (32-34). Furthermore, in the literature

available, variability exists in the real world with respect to adoption/de-adoption and it does not

always follow the evidence. For example, many of the severe ARDS adjuvants improve

oxygenation. Despite the lack of association between oxygenation improvement and mortality (5,

22), physicians are likely to reach for these adjuvants for the reassurance provided by improving

oxygenation. Other factors that may also drive adoption and de-adoption include experience

with the treatment, cost, availability, perceived risk, and patient comfort (32) (Figure 2). Lung

protective ventilation, which has consistently demonstrated a mortality benefit across a series of

trials, has not yet achieved widespread adoption in critical care (5, 34, 35). De-adoption of tight

glycemic control, has also been slow despite evidence of harm (33). However, this is not always

the pattern. There are other examples in critical care of rapid de-adoption as was the story of the

pulmonary arterial catheter following the observational study by Connors et al (36). Provocative

editorials, associated press and possibly the increase in non-invasive hemodynamic monitoring

potentially contributed to the rapid drop in use noted. Non evidence-based factors that impact

adoption/de-adoption include benefits/risk, feasibility, applicability and physician preferences

(32). When confidence in the evidence is lacking or if inconsistencies arise, these non-evidence

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factors drive patterns of use to a greater degree. Furthermore, the role of evidence in rescue

therapy becomes less clear and factors that drive adoption/de-adoption likely focus more on

physician preferences.

1.1.5 Conclusions

This section highlights adjuvants to standard mechanical ventilation for ARF and specifically

ARDS patients, the limited evidence base for the use of many of these adjuvants, and the

available data regarding how they are deployed in current practice. The current state of data

surrounding use has predominantly been cross sectional data (LUNG-SAFE) or self-reported

data on stated practice. Given the high costs in terms of equipment and personnel associated with

the use of many of these adjuvants, more research surrounding trends in use, how practice

changes in response to evidence, and factors that may influence adoption and de-adoption of

these adjuvants are needed. Arguably, the adjuvants that have been subject to the greatest debate

and scientific evaluation over the past decade include the use of ECMO, inhaled pulmonary

vasodilators, continuous neuromuscular blockading agents, high frequency oscillatory ventilation

and prone positioning, and therefore will be the focus of this analysis.

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Adjuvants to Mechanical Ventilation: Changes in Use and 2

Factors Associated with Use

2.1 Introduction

Acute respiratory failure (ARF) is associated with high morbidity and mortality and optimal

treatment strategies are incompletely defined. Interventions evaluated have predominantly

focused on patients with acute respiratory distress syndrome (ARDS); however, observational

data suggests they are used in patients with ARF even if the formal ARDS criteria are not met

(3). While lung protective ventilation and prone positioning have robust evidence supporting

their use, extracorporeal membrane oxygenation (ECMO), inhaled pulmonary vasodilators,

continuous neuromuscular blockading agents (cNMBA), and high frequency oscillatory

ventilation (HFOV) are used despite inconclusive evidence of benefit or possible harm (7, 21,

22, 25, 27-29, 37-39). As debates on adjuvant use continue and ongoing trials attempt to

establish effectiveness (NCT01470703, NCT02509078),(40) clinicians face daily decisions on

when to initiate these treatments.

The LUNG-SAFE study provides insight into ARF incidence, ARDS under-recognition, and

current management (3). However, LUNG-SAFE focused on academic medical centers and was

not designed to evaluate the use of treatments over time. A better understanding of factors

associated with adjuvant use across a broad range of hospitals, how their use is affected by

landmark publications, and what drives adoption/de-adoption is important to inform daily

clinical decisions and policies until further evidence becomes available.

2.2 Materials and Methods

We performed a retrospective cohort study of adults (≥18 years) discharged from a United States

(US) hospital between July 2008-June 2013 using the Premier Perspective® Hospital Database

(Charlotte, NC and Washington, DC) (41). Premier is a voluntary fee-supported database that

was developed as a healthcare performance improvement alliance and includes over 500

hospitals. It represents a sample of structurally and geographically diverse hospitals and

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approximately 15-20% of hospital discharges nationwide. In addition to containing discharge

data, it contains complete billing information with date-stamped logs of all charges (40).

2.2.1 Study Population and Cohort Creation

After removing hospitals with missing billing data, we included any adult patient who received

invasive mechanical ventilation and had a primary diagnosis of ARF–defined by the presence of

an International Classification of Disease, 9th

Edition, Clinical Modification (ICD9-CM) code

for ARF or ARDS (518.81, 518.82, 518.84, 518.5, 799.1, 786.09) (7, 42-44). Given the potential

for low sensitivity using the ARDS codes alone as well as high reports of use of adjuvants across

the ARF population (3, 44), we also included those identified as having a direct infectious or

direct non-infectious cause of ARF using ICD-9-CM codes (Table 2) (1). To avoid capturing

indications for adjuvant use outside of ARF, patients with a code for pulmonary hypertension,

cardiac surgery or transplantation were excluded (Table 2). Patient’s extubated alive within 24

hours of mechanical ventilation were also excluded. Research ethics approval was obtained from

the institutional review boards at Sunnybrook Health Sciences Center and Albert Einstein School

of Medicine.

2.2.2 Outcomes

We identified each adjuvant of interest using the hospital charges and/or ICD9-CM codes.

ECMO was identified using ICD9-CM codes 39.65 (ECMO) and 39.66 (percutaneous ECMO)

(45). Pulmonary vasodilators—including inhaled NO and inhaled epoprostenol (off label use)—

were identified using hospital charge terms. Continuous NMBA (atracurium, cisatracurium,

doxacurium, mivacurium, pancuronium, rocuronium, or vecuronium) was defined by charges for

at least two days at a dose over 24 hours that could achieve continuous paralysis (intermittent

bolus or continuous infusion) (46). We selected this dose to replicate the use of NMBA for ARF

as opposed to short-term use for procedures (Appendix Table 1). In sensitivity analyses, we

evaluated 1 day of cNMBA, continuous cisatracurium and any use of NMBA. We set out to

capture HFOV using the hospital billing term for the circuit specific to the SensorMedics

3100A/3100B (Viasys Healthcare, Yorba Linda, California USA); but concerns of undercoding

led us to exclude HFOV. Prone positioning was also not identifiable through this dataset.

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Patient and Hospital Data

We collected data on patient demographic, insurance status, Elixhauser comorbidities (47), and

clinical variables (e.g. dialysis, vasopressors). Hospital data included geographic location, bed

size, urban/rural location, and academic status.

2.2.3 Statistical Analysis

Patient and hospital level characteristics were summarized across the entire cohort and for

patients who received each adjuvant. Proportions were used for categorical and means (standard

deviation) or medians (interquartile ranges) for continuous variables as appropriate.

First, we evaluated rates of use of each adjuvant per 1000 persons per year by dividing the

number of patients with adjuvants by the total number of patients with ARF that year (x1000).

For each adjuvant, we used Poisson regression (48) to estimate the annual incidence rate ratio

and 95% confidence interval over the study period (reference year 2008), adjusted for age and

gender and clustered by hospital (49, 50). We hypothesized that ECMO and cNMBA use would

increase and that inhaled NO would be replaced with inhaled epoprostenol over time.

Second, we evaluated the impact of landmark studies on rates of use over time using segmented

regression analysis of an interrupted time series. A segmented regression analysis allows the

evaluation, in statistical terms, of how much a publication affects monthly rates of use. Segments

were defined by major landmark publications for each adjuvant (51) and the time series was the

monthly rates of use. A sufficient number of time points before and after the publication is

needed to conduct segmented regression analysis and generally 12 data points before and after is

recommended and was present for each of these analyses (51). Segmented regression answers

two different questions. First, if publication of the landmark study causes an immediate change

in use, it will be detected as a change in the intercept of the fitted regression line. Second, if

publication causes a change in use over time, the slope of the regression line will be different

from that time point compared to prior to that time point. Landmark studies published over this

time period were determined, a priori, by journal impact factor and evidence quality (Table 3):

for (1) ECMO—the Conventional Ventilator Support vs. Extracorporeal Membrane Oxygenation

for Severe Adult Respiratory Failure (CESAR) trial published on October 2009 (29)

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demonstrating transportation to a specialized center for ECMO consideration was associated

with improved disability free-survival at 6 months; (2) inhaled pulmonary vasodilators—the

Cochrane Collaboration meta-analysis published on July, 2010 (52) showing NO had no

statistically significant effect on mortality and appeared to increase renal injury risk; and (3)

cNMBA—the randomized trial published September 2010 demonstrating a survival benefit from

the early continuous cisatracurium administration in moderate-severe ARDS (8).

We evaluated patient and hospital level factors, determined a priori, associated with each

adjuvant using logistic regression. One of the fundamental assumptions of logistic regression,

that each observation is independent, may not hold true in this cohort due to potential clustering

at the hospital level. Given this, the analysis was fitted with generalized estimating equations to

properly account for the violation of the independence assumption due to the correlation between

outcomes within the cluster. Generalized estimating equations as opposed to multi-level

modeling was chosen to account for clustering given our interest in adjusting for the average

impact of hospitals on rates of use; while the specific relationship between detailed hospital

variation and the outcomes seen was not the primary focus. Physician level data was not

available in this dataset.

Adjuvant specific analyses were conducted only in hospitals capable of using that adjuvant—

defined as those hospitals that used the adjuvant at least once over the study period. It was

assumed that all hospitals could administer NMBAs. Statistical analyses were performed using

Stata 13.0 (StataCorp LP, College Station, TX). Results were considered statistically significant

at p<0.05.

2.2.4 Sensitivity Analyses

We conducted 5 sensitivity analyses were conducted to assess the robustness of the results. First,

to address the potential for hospitals leaving/entering the database, we repeated the primary

analysis restricted to hospitals contributing data in all study years. Second, we repeated the

segmented regression analysis excluding data from the H1N1 influenza epidemic year of 2009 to

ensure that temporal trends were not confounded by this unusual event. Third, since severity of

illness data are limited in the Premier Database, we restricted the analysis to patients who died

assuming that this stratifies the population to those with a high severity of illness and confirmed

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that the changes noted were similarly robust in this analysis (36, 53). Fourth, to further focus on

a population more representative of ARDS, we limited the analysis to those patients who were

intubated within the first two days of hospitalization and had the combined diagnostic codes for

severe sepsis, pneumonia and respiratory failure (7). We did not restrict this analysis to ARDS

codes alone given the high proportion of ARF patients who undergo adjuvant use in

unrecognized ARDS (3). For our primary analysis, we modeled year as a categorical variable to

evaluate changes over time; however, we also evaluated it as a continuous variable in order to

evaluate a trend over this time period. In an additional analysis, we evaluated a ―tracer

condition‖, the use of pulmonary artery catheters, whose temporal trends we anticipated would

be decreasing to validate the observed trends (36, 54).

2.3 Results

2.3.1 Cohort Assembly and Overview

Over the study period, 514,913 patients across 543 hospitals met the definition of ARF (Table 4

and Figure 3). The majority of patients were from urban centers (89%, n = 458,272) with 44%

(n=226,561) admitted to academic centers and 50% (n=257,457) to large hospitals (≥ 400 beds).

Pneumonia was the most frequent cause of ARF; 73% (n=375,886) received invasive mechanical

ventilation within the first 2 days of admission and 56% (n=288,351) received vasopressors.

Hospital mortality was 33% (n=169,921).

There were 12,146 adjuvants used among 11,567 patients (2.3% of patients), with most receiving

only one adjuvant (95%, n=11,006) (Table 5). cNMBAs were the most frequently used adjuvant

(n=10,073 cases, 2%), followed by inhaled pulmonary vasodilators (n=1,878, 1% in capable

hospitals, 0.4% entire cohort), and ECMO (n=195, 0.2% in capable hospitals, 0.04% entire

cohort). When two adjuvants were used, cNMBAs were used in 95% (n=474) and inhaled

pulmonary vasodilators were used in 93%. (n=465). When all three adjuvants were used in

combination, cNMBAs were most frequently used first (median (IQR) first day 1 (1-2)) followed

by inhaled pulmonary vasodilators (median (IQR) first day 3 (1-8)) and ECMO (median (IQR)

first day 4 (1-10)).

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2.3.2 Changes Over Time

Extracorporeal Membrane Oxygenation

One-hundred ninety-five patients (0.2%) received ECMO. Only 62 (11%) hospitals had at least

one ECMO case over the study period. ECMO-capable hospitals were predominantly large

(61%; 38/62), urban (97%; 60/62), academic (61%; 38/62) centers. The mean (SD) age of

ECMO patients was 46 (±17). Hospital mortality was 54% (n=106) (Table 6). ECMO use

increased significantly over the time period (Figure 4a); there was no difference in the rate of use

before and after the publication of the CESAR trial (29) (Figure 5a). These results did not change

after eliminating the 2009 data.

Inhaled Pulmonary Vasodilators

Inhaled pulmonary vasodilators were used in 1,878 patients (1% of patients in inhaled

vasodilator-capable hospitals). Twenty-two percent of hospitals (119) had at least one case of

inhaled pulmonary vasodilator use (inhaled NO or inhaled epoprostenol). These patients were

predominantly admitted to larger (≥ 400 beds, 73%, n = 1,371), urban (97%, n=1,821), and

academic (72%, n=1,352) centers. Their mean (SD) age was 55 (± 18) with 58% (n=1,087)

receiving inhaled NO. Hospital mortality was 59% (n=1,108) (Table 6).

Inhaled NO use did not change over the study time period (Figure 4b); there was no change in

use after publication of the Cochrane review (Figure 5b) (52). The results did not change after

eliminating the 2009 data. The use of inhaled epoprostenol increased over the time period

(Figure 4c). However, following the Cochrane publication which focused on NO (52), the rate

of growth in epoprostenol use diminished significantly (Figure 5c). The results did not change

after eliminating the 2009 data.

Continuous Neuromuscular Blockading Agents

Continuous NMBAs (≥2 days) were used in 10,073 patients (2% of all patients in the cohort)

with a mean (SD) age of 51 (± 17). The majority of patients were admitted to urban hospitals

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(94%, n = 9,469) and only 50% (n=5,037) were admitted to academic hospitals. Cisatracurium

was the most commonly used agent (52%, n = 5,238). The median (IQR) duration of continuous

paralysis was 3 days (2-5) with a median first day of initiation being day 2 (1-4) of mechanical

ventilation for all agents. Hospital mortality was 43% (n=4,331) (Table 6).

There was an isolated increase in use of cNBMA in 2009; however, following that year, there

was no consistent increase in use over time (Figure 4d). Upon evaluating the impact of the

cNMBA trial, no change was noted in the yearly cohort and after the 2009 data was removed

(Figure 5d) (8). These results were robust when restricted to 1 day of cNMBA, any use of

NMBA, and cisatracurium specifically (Table 7).

Sensitivity Analyses

The results were similar when limited to hospitals who contributed data for the entire study

duration and amongst patients who died (Table 7). In our ARF cohort designed to replicate an

ARDS population, the overall number of patients and adjuvants used was significantly reduced.

Because of this, there was some variability compared to the above results, however, none of the

rates of use of the adjuvants decreased overtime (Table 7). When year was modeled as a

continuous variable, there was no time trend overall in ECMO use seen (Table 7); however, it is

possible that this absence of a statistically significant linear time trend may be attributable to the

absence of an ordered increase given the H1N1 outlier. As expected, we observed a decrease in

the rate of pulmonary artery catheter use (Figure 6 ).

2.3.3 Factors Associated with Adjuvant Use

A diagnosis of severe sepsis and vasopressor use were associated with higher likelihood of

receiving each adjuvant (Figure 7). Patient factors consistently associated with a lower likelihood

of receipt of each adjuvant included older age, non-private insurance status and undergoing

surgery during admission (Figure 7).

Mechanical ventilation within the first two days of hospitalization was associated with a higher

likelihood of receiving ECMO, whereas obesity and dialysis were more likely to be associated

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with inhaled NO and epoprostenol. An admission diagnosis of chronic renal failure was

associated with a decrease in use of inhaled NO (Figure 7).

Among ECMO-capable hospitals, patients were more likely to receive ECMO at larger (odds

ratio [OR] 1.01; 95% confidence interval [CI] 1.00-1.02) and non-academic hospitals (23

centers) (OR for academic hospital 0.39; 95% CI 0.25-0.62) (Figure 7a). In inhaled pulmonary

vasodilator-capable hospitals, one was more likely to receive epoprostenol at academic (OR

5.86; 95%CI 3.74-9.19) but less likely in larger hospitals (OR 0.99; 95% CI 0.99-1.00) (Figure

7d). No hospital specific characteristics were associated with NO use (Figure 7c). Finally,

cNMBAs were more likely administered in urban (OR 1.49; 95% CI 1.26-1.79) and academic

hospitals (OR 1.16; 95% CI 1.05-1.28) (Figure 7b).

2.4 Discussion

We investigated the use of four adjuvants for ARF and found variable rates of change in use over

the study period. As hypothesized, ECMO and inhaled epoprostenol use increased. However,

contrary to our hypothesis, rates of inhaled NO did not decrease and rates of cNMBA use were

unchanged. There was no immediate impact of landmark publications with the exception of

inhaled epoprostenol. Patient- and hospital-level factors associated with use vary considerably by

adjuvant.

Previous studies have evaluated self-reported use of adjuvants (9, 18) and historic utilization

patterns (20). The LUNG-SAFE study was a cross sectional study that characterized

management of 2,377 ARDS patients (3). The higher use of adjuvants reported may be

attributed, in part, to the LUNG-SAFE cohort being clearly defined as ARDS and the study’s

ability to stratify by hypoxemia. The data were also collected during the winter months when the

number of severe ARDS cases, and thus adjuvant use, may have been higher. Recruitment for

LUNG-SAFE was achieved through announcements by ICU societies, which could bias results

towards centers with greater enthusiasm surrounding ARDS and the use of adjuvant therapies.

To our knowledge, this study is the largest to characterize changes in use and factors associated

with adjuvant use for all forms of ARF. This study is unique in that it captures a recent period

during which there was a lot of scholarly activity surrounding adjuvants thus enabling us to

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explore adoption/de-adoption. We found the adoption of a complex and costly adjuvant for

which there is some evolving evidence (ECMO), no adoption of a seemingly simple, widely

available adjuvant for which there exists some evidence of benefit (cNMBA), no de-adoption of

an adjuvant for which there has been consistent evidence of no benefit and some signal for harm

(NO), and adoption of an adjuvant for which there has been minimal evidence (inhaled

epoprostenol). Understanding physician preferences and what drives them is complex yet critical

to influencing care decisions (33). Evidence does not always drive adoption; non-evidence

factors such as patient characteristics, perceived benefits/risks, feasibility, and physician

preference may play a role (32). Slow adoption for seemingly useful interventions has been seen

with lung protective ventilation (34). While de-adoption of ineffective interventions tends to be

slow (33) as the epidemiology of pulmonary artery catheter use shows, it is possible (36, 54).

The appeal of a novel intervention or the observed improvements in oxygenation (despite lack of

association with mortality), likely contribute to ECMO use and the lack of de-adoption of NO,

respectively. For cNMBAs, absence of adoption could be attributed to the uncertainty

surrounding benefit, (55) the absence of instant patient improvement, or concerns about harm. It

is likely that rescue is an important driver of decisions in managing patients with ARF and severe

hypoxemia. In cases where physicians perceive that patients are at imminent risk of death, cost

and lack of evidence may play a smaller role in decision-making (56).

Strengths and Limitations

This study has several strengths. We used a large, well-defined dataset reflecting real world

practice across a diverse group of hospitals. The results were robust to a number of sensitivity

analyses that tested the effect of an outlier H1N1 year and severity of illness. Finally, we were

able to replicate expected changes in practice over time: a reduction in use of pulmonary artery

catheters and an increased use of all adjuvants in 2009 coincident with the H1N1 influenza

epidemic. These findings are reassuring that we were capturing true trends rather than changes in

documentation or coding.

There are several limitations to this study. First, some ICD-9-CM validation studies demonstrate

low sensitivity but high specificity of claims data thus potentially underestimating the frequency

of diseases/interventions (7, 36). The ECMO numbers, in particular, appear small; this could be

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due to under-coding or capturing a subset of low-volume ECMO centers. We think this is

unlikely as ECMO has important billing implications in the US. However, if either were true,

this would potentially underestimate the rate of rise and likely not negate the positive trend

noted. The discrepancy noted between year evaluated as a categorical and continuous variable

may be attributable to the H1N1 outlier year, which eliminates an ordered increase in use when

year is evaluated continuously. Alternatively, there may be no incremental linear increase over

the years; however, there may exist changes over time that were more pronounced in the most

recent years as was found in the categorical analysis.

Second, our ability to identify the severity of ARF was limited given the lack of ICU level

physiology variables. This precluded us from performing stratification across strata of varying

severities of illnesses. This would bias the rates of use of adjuvants to a lower estimate, but we

feel it would not affect our exploration of trends over time and factors associated with use. The

decedent analysis, which restricts the analysis to those sick enough to die, demonstrated similar

results.

Thirdly, it is plausible that misclassification could have arisen with regard to indications for the

adjuvants of interest. We attempted to minimize this by excluding any alternative indications for

the adjuvants of interest. While this minimizes its generalizability (i.e., excluded transplant and

cardiac surgery), it increases our confidence that we were capturing its use primarily for

respiratory failure.

Fourthly, selection bias may exist in the subset of hospitals that contribute to the Premier

database (i.e., more prone to use evidence based therapies or new innovations). However, we felt

that this would be minimized given the large number of hospitals. After reviewing the

distribution of hospitals that contribute data to Premier, it is possible that the database may not

be generalizable. It favored urban centers and centers from the Southern US; however, even

within this region, there was variability with respect to hospital size and academic status. In

addition, patterns of adoption and de-adoption, may be different in hospitals outside of the US

given that physician preferences appears to be a large driver of use.

Finally, for evaluating changes in use, even if there existed a true of change in response to the

evidence, it is possible that the landmark publication date may not result in an immediate change.

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It is possible that the time period being evaluated was not sufficiently long to see a change where

a change may exist particularly if the change was a more gradual one in response to the evidence.

Often times, landmark publications are affiliated with presentations that international meetings

which occur at a different time point. This could have also led to a different time point that was

not captured in this analysis. We also do not know how adoption and de-adoption changes in

extreme clinical circumstances where death may be imminent such as the application of adjuvant

strategies.

3.0 Conclusions and Future Directions

This study highlights real world variability in adjuvant use; variability which likely reflects, in

part, the limits of available evidence. However, even when the evidence base is strong, adoption

and de-adoption practices are not solely driven by evidence with many factors affecting bedside

decision-making. Extreme clinical circumstances may also have an impact on decision making

regarding use and has not been evaluated.

In conjunction with trying to develop a stronger body of evidence for the adjuvants evaluated,

developing a better understanding of factors associated with adjuvant use is necessary.

Understanding what drives adoption and de-adoption at the patient, physician and hospital level

will be important to drive knowledge translation activities that could have an impact on bedside

application. Only then can we safely encourage adoption of effective interventions and promote

de-adoption of ineffective interventions.

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Table 1. Reported Use for Common Adjuvants in Acute Respiratory Failure

Adjuvant

Recent Evidence* Reported Use in Acute Respiratory Failure

Pharmacologic

Continuous

Neuromuscular

Blocking Agents

Papazian L, et al. (2010)

Neuromuscular blockers in early

acute respiratory distress syndrome. N

Engl J Med. 2010;363(12):1107-17

(Pre-Papazian Trial) 15-23% use in ARDS (7, 9)

(Post-Papazian Trial) LUNG-SAFE: 37.8 %

reported use in severe ARDS (3)

Diuretics Wiedemann HP, et al (2006)

Comparison of two fluid management

strategies in acute lung injury. N Engl

J Med 354: 2564-2575

Grissom CK, et al (2015)

Fluid management with a simplified

conservative protocol for acute

respiratory distress syndrome. Crit

Care Med. 43 (2): 288-295

Administered in 39% of patients with ARDS

(single center retrospective study) (12)

Self-reported use 70% of patients with ARDS

(survey of intensivists) (9)

Corticosteroids Meduri G, et al. (2007)

Methylprednisolone infusion in early

severe ARDS: results of a randomized

controlled trial. Chest. 131: 954-963

Steinberg K, et al. (2006)

Efficacy and safety of corticosteroids

for persistent acute respiratory

distress syndrome N Eng J Med. 354:

161-84

Of 70% of UK physicians surveyed who used

corticosteroids in ARDS: 30% reported

initiating early in ARDS (≤7 days), 53% reported

initiating late in ARDS (>7 days) (9)

LUNG-SAFE**

: 17.3% reported use across all

ARDS, 23.3% severe ARDS (3)

Inhaled Nitric

Oxide

Adhikari NK, et al (2014)

Inhaled nitric oxide does not reduced

mortality in patients with ARDS

regardless of severity: systematic

review and meta-analysis. Crit Care

Med. 42 (2): 404-412

29-44% (9, 18, 20)

LUNG-SAFE: 7.7 % reported use¶ across all

ARDS, 13.0% severe ARDS (3)

Non-pharmacologic

Prone Positioning Guerin C, et al (2013)

Prone positioning in severe acute

respiratory distress syndrome. New

Engl J Med. 368: 2159-2168

(Post- Guerin Trial ) LUNG-SAFE: 7.9% across

all ARDS, 163% severe ARDS (3)

High Frequency

Oscillatory

Ventilation

Ferguson N, et al (2013)

High frequency oscillation in early

acute respiratory distress syndrome.

(Pre-Ferguson/Young Trials) 7-50% (rescue

therapy) (9, 20)

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New Engl J Med 368: 795-805

Young D, et al (2013)

High frequency oscillation for acute

respiratory distress syndrome. New

Engl J Med 386: 806-813

(Post-Ferguson/Young Trials) LUNG-SAFE:

1.5% in severe ARDS (3)

Extracorporeal

Membrane

Oxygenation

Peek G, et al (2009)

Efficacy and economic assessment of

convention ventilator support vs.

extracorporeal membrane

oxygenation for severe adult

respiratory failure. Lancet.374 (9698):

1351-1363

12 fold increase in rate of use over the past

decade (2004-2014) (31)

LUNG-SAFE: 3.2 % across all ARDS, 6.6%

severe ARDS (3)

ARDS Acute Respiratory Distress Syndrome

LUNG SAFE The Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure *Evidence: Trials or systematic reviews/meta analyses over the past 10 years

** high corticosteroids dose defined as equivalent to 1 mg/kg methylprednisone

¶ all inhaled vasodilators (inhaled nitric oxide)

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Table 2: Inclusion and Exclusion ICD-9 CM codes

Inclusion ICD9 CM Codes

Mechanical Ventilation 96.70, 96.71, 96.72

Respiratory Failure 518.82 , 518.81 , 518.84 , 799.1

DIRECT INFECTIOUS CAUSES OF ARDS

480.0-480.9 , 481 , 482.0-482.9 , 483.0, 483.1, 483.8, 484, 485 , 486 , 487.0

, 011, 012, 018, 114 , 115 , 116, 510, 513

DIRECT NON-INFECTIOUS CAUSES OF ARDS

987.0-987.9, 986, 507.0, 997.32, 022.1 , E910.0,1,3,4,8,9, 861.00-861.32,

958.0 , 958.1 , 417.8 , 518.7

Exclusion ICD9 CM Codes

Pulmonary Hypertension 416.0, 416.8

Cardiac Surgery 39.61 , 35.00-35.09, 36.00-36.09, 37.31-37.37, 37.41, 441.00-441.9

Transplant V42.0-42.7, V42.83, 37.51 , 33.50-33.6 , 50.5 , 55.61, 55.69 , 52.8, 41.00-

41.09

ARDS Acute Respiratory Distress Syndrome

ICD-9-CM International Classification of Disease, 9th Edition, Clinical Modification

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Table 3: Landmark Studies Evaluated

Adjuvant Reference Publication Date Results Comments

ECMO Peek G et al. Efficacy and

economic assessment of

conventional ventilatory

support versus

extracorporeal membrane

oxygenation for severe adult

respiratory failure (CESAR):

a multicenter randomized

controlled trial. Lancet.

2009;374:1351-63

October 2009 Transport to an

ECMO capable

center was

associated with

improved 6 month

disability free

survival

Less compliance

with lung protective

ventilation in control

arm. Not all patients

who were

transported to the

specialized center

for ECMO

underwent ECMO

Inhaled

Pulmonary

Vasodilators

Afshari A et al. Inhaled

nitric oxide for acute

respiratory distress syndrme

(ARDS) and acute lung

injury in children and adults.

The Cochrane

Collaboration. 2010 (7).

July 2010 After pooling the

data from 14

randomized

controlled trials,

inhaled nitric oxide

had no statistically

significant effect on

mortality and

appeared to increase

the risk of renal

injury amongst adult

patients with ARDS

Unclear of its role as

a rescue therapy. In

a later meta-analysis,

evaluating its impact

on varying severities

of illness, there was

no benefit across

more severe ARDS

cohorts (21)

cNMBA

Papazian L, et al.

Neuromuscular blockers in

early acute respiratory

distress syndrome. N Engl J

Med. 2010;363(12):1107-17

September 2010 The early,

continuous

application of

cisatracurium for 48

hours in moderate to

severe ARDS was

associated with an

improved adjusted

90 day mortality

Some uncertainty

followed with

respect to the

mechanism by which

paralysis lead to the

improved late

mortality

ECMO: extracorporeal membrane oxygenation cNMBA: continuous neuromuscular blockading agents

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Table 4: Baseline Demographic Characteristics (2008-2013)

N = 514, 913 Patients

BASELINE DEMOGRAPHIC CHARACTERISTICS

Age (mean ± SD) 62 ((± 17)

Gender (Female, n (%)) 247,158 (48)

Race (White, n (%)) 334,693 (65)

BASELINE CLINICAL VARIABLES

No. Elixhauser Comorbidities, median (IQR) 0 (0-0)

ARDS risk factor, n (%):

Pneumonia 278,053 (54)

Non-Pulmonary Sepsis 72,087 (14)

Non-Infectious SIRS 25,745 (5)

Trauma 56,640 (11)

Mechanical Vent in first 2 days (n (%)) 375,886 (73)

Vasopressors (n (%)) 288,351 (56)

In-Hospital Dialysis (n (%)) 56,640 (11)

ADJUVANT CHARACTERISTICS

Extracorporeal Membrane Oxygenation (n (%))* 195 (0.2)*

Inhaled Pulmonary Vasodilators (n (%))* 1,878 (1.0)*

Inhaled Nitric Oxide (n (%))* 1,087 (0.7)*

Neuromuscular Blockading Agents** (1 day) (n (%)) 20,077 (3.8)

Neuromuscular Blockading Agents** (2 days) (n (%)) 10,073 (2.0)

OUTCOMES

Duration of Mechanical Vent (survivors, days, median IQR) 4 (3-9)

Length of ICU Admission (survivors, days, median IQR) 6 (3-12)

Hospital Mortality (n(%)) 169,921 (33)

Cost (mean ±SD) ¶¶ $27,979 ($14,468-$51,980)

PATIENT DISTRIBUTION ACROSS HOSPITALS

Urban (n (%)) 458,272 (89)

Teaching (n (%)) 226,562 (44)

Bed size (n (%))

Large ≥ 400 beds 257,457 (50)

Medium 200-399 beds 190,518 (37)

Small < 200 beds 66,939 (13)

Location (n (%))

Midwest 92,684 (18)

Northeast 62,684 (18)

South 242,009 (47)

West 87,535 (17) IQR – interquartile range; No. – number; SD – standard deviation, * % reported across hospitals capable of employing that adjuvant, **estimated minimum dosage that can attain continuous paralysis/24 hours, ¶28 day mortality assumes that those discharged before 28 days were alive at 28

days, ¶¶ total patient cost for hospitalization, all patients included

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Table 5: Adjuvant Frequencies

Total Adjuvants (n (%)) 12,146

1 11,006 (2)

2 499 (0.1)

3 40 (<0.01)

One Adjuvant (n (%))

Continuous neuromuscular blockading agents 9537 (86)

Inhaled pulmonary vasodilators 1373 (12)

Extracorporeal membrane oxygenation 96 (1)

Two Adjuvants (n (%))

Continuous neuromuscular blockading agents 474 (95)

Inhaled pulmonary vasodilators 465 (89)

Extracorporeal membrane oxygenation 59 (11)

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Table 6: Patient and Hospital Characteristics According to Adjuvant

ECMO IPV cNMBA

PATIENT CHARACTERISTICS

n=195 n=1,878 n=10,073

Age (mean ± SD) 46 (17) 55 (18) 51 (18)

Race (n (%) Caucasian) 127 (64) 1,052 (56) 6,346 (63)

Gender (n (%) Female) 86 (44) 789 (42) 3,727 (37)

Insurance Status (n (%))

Private 96 (49) 657 (35) 3,123 (31)

Medicare 41 (21) 695 (37) 3,324 (33)

Medicaid 49 (25) 338 (18) 2,015 (20)

Elixhauser Comorbidities (median

IQR)

0 (0-0) 0 (0-0) 0 (0-1)

Immunocompromised (n (%)) 2 (1) 94 (5) 403 (4)

No. Hospitals 62 119 543

Vasopressor Use (n (%)) 167 (87) 1,615 (86) 8,159 (81)

In-Hospital Dialysis (n (%)) 45 (23) 488 (26) 1,813 (18)

In-Hospital Mortality (n (%)) 105 (54) 1,108 (59) 4,331 (43)

Cost per hospitalization (mean USD) 97,501 74,292 61,579

HOSPTIAL CHARACTERISTICS*

Bed size (mean ± SD) 626 (255) 528 (210) 475 (225)

Teaching (n (%)) 140 (72) 1,352 (72) 5,037 (50)

Urban (n (%)) 193 (99) 1,821 (97) 9,469 (94) cNMBA – continuous neuromuscular blockading agents

ECMO – extracorporeal membrane oxygenation

IPV – inhaled pulmonary vasodilators IQR – interquartile range

No. - number

SD – standard deviation USD – United States Dollars; *number of patients across hospital characteristics

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Table 7: Changes Over Time Sensitivity Analyses

Hospitals Present Entire

Cohort

100% Mortality Cohort Sensitivity Analysis

ECMO

Year RR (95% CI) Year RR (95% CI) Year RR (95% CI)

2008 (reference 1.0) 2008 (reference 1.0) 2008 (reference 1.0)

2009 2.2 (0.9-5.6) 2009 2.3 (0.8-6.4) 2009 7.4 (1.1-51.4))

2010 1.4 (0.6-3.3) 2010 1.4 (0.5-3.9) 2010 1.3 (0.1-15.0)

2011 2.2 (0.9-5.5) 2011 1.8 (0.7-4.4) 2011 2.6 (0.3-21.6)

2012 3.9 (1.9-8.0) 2012 2.5 (1.2-5.3) 2012 3.6 (0.4-30.1)

2013 3.2 (1.5-6.9) 2013 2.8 (1.1-7.0) 2013 7.4 (0.9-61.1)

Analysis using year as a continuous variable: RR 1.16 95% CI 0.98-1.37


Cohort


Inhaled Nitric Oxide



2009 1.1 (0.8-1.5) 2009 1.6 (1.0-2.5) 2009 1.6 (0.8-3.2)

2010 1.0 (0.7-1.5) 2010 1.3 (0.8-2.2) 2010 0.8 (0.4-1.8)

2011 1.2 (0.8-1.8) 2011 1.5 (0.9-2.7) 2011 1.4 (0.6-3.0)

2012 1.0 (0.5-2.1) 2012 1.2 (0.6-2.5) 2012 1.1 (0.5-2.6)

2013 1.0 (0.5-2.0) 2013 1.3 (0.6-2.6) 2013 1.3 (0.5-3.2)



Cohort


Inhaled Epoprostenol



2009 1.8 (1.1-3.0) 2009 1.6 (0.8-3.0) 2009 1.2 (0.5-2.7)

2010 2.5 (1.1-5.3) 2010 2.3 (1.0-5.4) 2010 1.9 (0.6-5.3)

2011 2.0 (0.8-5.4) 2011 2.2 (0.8-6.2) 2011 1.7 (0.6-4.5)

2012 1.9 (0.8-4.1) 2012 2.6 (1.0-6.0) 2012 1.8 (0.7-5.0)

2013 1.8 (0.8-4.1) 2013 2.7 (1.1-6.0) 2013 2.9 (0.9-8.4)



Cohort


cNMBA



2009 1.1 (1.0-1.3) 2009 1.2 (1.1-1.4) 2009 1.1 (0.9-1.3)

2010 1.0 (0.9-1.2) 2010 1.1 (0.9-1.3) 2010 0.9 (0.7-1.1)

2011 1.1 (0.9-1.3) 2011 1.3 (1.1-1.5) 2011 0.9 (0.8-1.2)

2012 1.1 (0.9-1.2) 2012 1.3 (1.1-1.5) 2012 0.9 (0.7-1.1)

2013 1.0 (0.9-1.2) 2013 1.2 (1.0-1.5) 2013 0.9 (0.7-1.1)


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cNMBA 1 day* Cisatracurium 2 days** Any dose/use NMBA

cNMBA SENSITIVITY



2009 1.1 (1.0-1.3) 2009 1.1 (0.9-1.2) 2009 1.0 (0.9-1.0)

2010 0.9 (0.9-1.1) 2010 1.1 (0.9-1.3) 2010 1.0 (0.9-1.0)

2011 1.0 (0.9-1.2) 2011 1.1 (0.9-1.3) 2011 1.0 (0.9-1.0)

2012 0.9 (0.8-1.1) 2012 1.1 (0.9-1.3) 2012 1.0 (0.9-1.0)

2013 0.9 (0.8-1.2) 2013 1.1 (0.9-1.2) 2013 1.0 (0.9-1.0) *dose to achieve continuous paralysis for 24 hours for 1 day only

** dose to achieve continuous paralysis for 24 hours for 2 days for cisatracurium only

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Figure 1: Adjuvants for Acute Respiratory Failure

Figure 1 depicts the spectrum of adjuvants to mechanical ventilation for acute respiratory failure across different severities of illness

29

29

Figure 2: Factors that Drive Decision Making

Figure 2 depicts factors that may influence clinician decision-making (32)

30

30

Figure 3: Cohort Creation

Adult in-patients

undergoing mechanical

ventilation

n = 736,488

Adult in-patients undergoing

mechanical ventilation with

respiratory failure

n = 663,303

Final Cohort for Analysis

n = 514,913

EXCLUDE

Pulmonary hypertension, transplant, cardiac surgery

(102,494)

Extubated alive after 24 hours of mechanical ventilation and discharged alive

(45,896)

EXCLUDE

No Mechanical Ventilation Billing Code (16,453)

Non-Respiratory Failure (56,732)

Figure 3 depicts the cohort assembly based upon inclusion and exclusion criteria

31

Figure 4: Age and Sex Adjusted Changes in Use of Adjuvants Over Time

Figure 4a depicts annual ECMO rates per 1000 persons per year using Poisson regression analysis

expressed as the incidence rate ratio.

32


Figure 4b depicts annual iNO rates per 1000 persons per year using Poisson regression analysis expressed

as the incidence rate ratio. Test for trend p= 0.88 evaluating year as a continuous variable.

33

33


Figure 4c depicts annual iEpoprostenol rates per 1000 persons per year using Poisson regression analysis

expressed as the incidence rate ratio.

34


Figure 4d depicts annual cNMBA rates 1000 persons per year using Poisson regression analysis

expressed as the incidence rate ratio

Figure 5: Impact of Landmark Publications on Changes of Use Over Time

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35

a) Extracorporeal Membrane Oxygenation

Figure 5a depicts the segmented regression analysis of changes in monthly rates in use of ECMO in

response to landmark publications (arrow specifies time point of publication)

36

36


b) Inhaled Nitric Oxide

Figure 5b depicts the segmented regression analysis of changes in monthly rates in use of iNO in


37

37


c) Inhaled Epoprostenol

Figure 5c depicts the segmented regression analysis of changes in monthly rates in use of

iEpoprostenol in response to landmark publications (arrow specifies time point of publication)

38

38


d) Continuous Neuromuscular Blockading Agents

Figure 5d depicts the segmented regression analysis of changes in monthly rates in use of cNMBA in


39

39

Figure 6: Changes in Use of Pulmonary Artery Catheter

Figure 6 depicts annual rates per 1000 persons per year over time and the incident rate ratio

using Poisson regression analysis

40

40

Figure 7a: Factors Associated With Adjuvant Use

Figure 7a depicts patient and hospital factors associated with ECMO adjuvant use using logistic

regression fitted with generalized estimating equations

41

41

Figure 7b: Factors Associated With Adjuvant Use

Figure 7b depicts patient and hospital factors associated with cNMBA adjuvant use using logistic


42

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Figure 7c: Factors Associated With Adjuvant Use

Figure 7c depicts patient and hospital factors associated iNO adjuvant use using logistic


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Figure 7d: Factors Associated With Adjuvant Use

Figure 7d depicts patient and hospital factors associated iEpoprostenol adjuvant use using

logistic regression fitted with generalized estimating equations

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44

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Appendix

Appendix Table 1: Determination of Continuous Neuromuscular Blockading Agent Dosing

Neuromuscular

Blockading Agent

Steingrub JS

et al dosage

LEXICOMP lower

infusion range

(mechanical

ventilation protocol)

LEXICOMP

multiple boluses

using 2x duration

to maintain

continuous

paralysis/24 hrs

Minimum dosage

suggestive of

continuous paralysis

chosen for our study

ATRACURIUM 100 mg 400 mg 1000 mg ≥ 400 mg / 24 hrs

CISATRACURIUM 40 mg 100 mg 168 mg ≥ 100 mg/ 24 hrs

ROCURONIUM 100 mg 800 mg 1000 mg ≥ 600 mg / 24 hrs

VECURONIUM 20 mg 84 mg 100 mg ≥ 80 mg / 24 hrs

PANCURONIUM 84 mg 25 mg ≥ 25 mg/ 24 hrs

ATRACURIUM

Infusion 0.24-1.2 mg/kg/hr (ICU paralysis to facilitate mechanical ventilation)

Bolus 0.40-0.50 mg/kg

Half Life ~20 minutes (terminal) (2 half lives 40 minutes (36 bolus doses in 24 hours)

Recovery Time 20-35 minutes 70 minutes- 1.2 hours 20 boluses / 24 hours

CISATRACURIUM

Infusion 0.06-0.18 mg/kg/hr (ICU paralysis to facilitate mechanical ventilation) (even smaller infusion ranges are

described 0.03)

Bolus 0.1-0.2 mg/kg

Half Life ~30 minutes (2 half lives 60 minutes (24 bolus doses in 24 hours)

Duration Recovery Time 20-35 minutes 70 minutes- 1.2 hours 20 boluses / 24 hours

ROCURONIUM


Bolus 0.60-1.0mg/kg

Half life ~60 minutes – 144 minutes (2 half lives 288 minutes 4.8 hours (5 bolus doses in 24 hours)

Duration ~30 minutes (2 x duration 60 minutes (24 boluses in 24 hours)

VECURONIUM


Bolus 0.08-0.10 mg/kg

Half life ~65-75 minutes (2 half lives 150 minutes 2.5 hours (9.6 bolus doses in 24 hours)

Duration ~25-40 minutes (2 x duration 80 minutes (18 boluses in 24 hours)

PANCURONIUM


Bolus 0.1-0.2mg/kg (Q1-3HRS)

Half life ~110 minutes (2 half lives 220 minutes 3.6 hours (7 bolus doses in 24 hours)

Duration ~60-100 minutes (2 x duration 200 minutes (7.3 boluses in 24 hours)

Steingrub JS, Lagu T, Rothberg MB, Nathanson BH, Raghunathan K, Lindenauer PK. Treatment with

neuromuscular blocking agents and the risk of in-hospital mortality among mechanically ventilated patients with

severe sepsis. Crit Care Med. 2014;42(1):90-6.

Lexicomp Online, Lexi-Drugs, Hudson, Ohio: Lexi-Comp, Inc; April 2014.

Consultation with Lisa Burry, Clinician Scientist and Clinical Critical Care Pharmacy Specialist, Mount Sinai

Hospital

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