ORIGINAL RESEARCH

Intuitive versus Algorithmic Triage

Alexander Hart, MD;1 Elias Nammour; 2 Virginia Mangolds, MSN, FNP-C, BSEd. RN, CEN;3
John Broach, MD, MPH3

Abstract
1. Department of Emergency Medicine, Beth Introduction: The most commonly used methods for triage in mass-casualty incidents
Israel Deaconess Medical Center, Boston, (MCIs) rely upon providers to take exact counts of vital signs or other patient parameters.
Massachusetts USA The acuity and volume of patients which can be present during an MCI makes this a time-
2. University of Massachusetts Medical consuming and potentially costly process.
School, Medical Education, Worcester, Hypothesis: This study evaluates and compares the speed of the commonly used Simple
Massachusetts USA Triage and Rapid Treatment (START) triage method with that of an “intuitive triage” method
3. Department of Emergency Medicine, which relies instead upon the abilities of an experienced first responder to determine the triage
University of Massachusetts Medical category of each victim based upon their overall first-impression assessment. The research team
School, Worcester, Massachusetts USA hypothesized that intuitive triage would be faster, without loss of accuracy in assigning triage
categories.
Correspondence: Methods: Local adult volunteers were recruited for a staged MCI simulation (active-
Alexander Hart, MD shooter scenario) utilizing local police, Emergency Medical Services (EMS), public ser-
Department of Emergency Medicine vices, and government leadership. Using these same volunteers, a cluster randomized
Beth Israel Deaconess Medical Center simulation was completed comparing START and intuitive triage. Outcomes consisted of
330 Brookline Avenue the time and accuracy between the two methods.
Boston, Massachusetts 02215 USA Results: The overall mean speed of the triage process was found to be significantly faster
E-mail: Alexhart1988@gmail.com with intuitive triage (72.18 seconds) when compared to START (106.57 seconds). This
effect was especially dramatic for Red (94.40 vs 138.83 seconds) and Yellow (55.99 vs
91.43 seconds) patients. There were 17 episodes of disagreement between intuitive triage
Conflicts of interest: Funding for the full-scale
and START, with no statistical difference in the incidence of over- and under-triage
exercise was provided by the Central
between the two groups in a head-to-head comparison.
Massachusetts Homeland Security Advisory
Conclusion: Significant time may be saved using the intuitive triage method. Comparing
Council (Worcester, Massachusetts USA).
START and intuitive triage groups, there was a very high degree of agreement between
Funding for the research aspect of the project
triage categories. More prospective research is needed to validate these results.
was provided by the University of Hart A, Nammour E, Mangolds V, Broach J. Intuitive versus algorithmic triage. Prehosp
Massachusetts Medical School (Worcester, Disaster Med. 2018;33(4):355–361.
Massachusetts USA). The authors declare no
conflicts of interest.

Keywords: disaster; EMS; mass casualty; triage Introduction

Abbreviations: Mass-casualty triage is the process by which large numbers of patients affected by a single
EMS: Emergency Medical Services incident are sorted and ordered for transport and treatment from the scene of a mass-casualty
FSE: full-scale exercise incident (MCI). By definition, disasters occur when a scarcity of at least one available resource
MCI: mass-casualty incident limits immediate treatment and transport of all victims.1 Triage allows the disbursement of
START: Simple Triage and Rapid Treatment resources including responders, transport vehicles, equipment, and medications in a manner
which will provide the greatest benefit to the greatest number of people.1,2
Received: December 28, 2017 Currently, MCI triage in the US is typically accomplished by using an algorithm which
Revised: March 25, 2018 measures certain physiologic parameters, and established normal values for these para-
Accepted: April 27, 2018 meters, to determine which patients are treated first and which can wait for treatment
without significant risk of deterioration.3,4 There is broad agreement among professional
doi:10.1017/S1049023X18000626 stakeholder organizations in the US that triage methodologies should conform to a variety
of criteria known as the Model Uniform Core Criteria (MUCC) for MCI triage. These
criteria include flexibility, simplicity, broad applicability, and basis in the best available
evidence, among many others.5,6 Most triage systems measure circulation, respiratory
effort, and mentation as the basis upon which triage decisions are made. Most methods use
familiar categories to differentiate patients into those who are either dead or expected to die
no matter the intervention (Expectant/Dead or Black); those requiring rapid initiation of
critical care (Immediate or Red); other injuries which require significant intervention but
which may tolerate a delay in care (Delayed or Yellow); and minimal injuries requiring only
basic medical care or no care at all (Minor or Green).2,5 The most commonly used MCI

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 356 Intuitive vs Algorithmic Triage

triage protocol in the US is the Simple Triage and Rapid Treat- and clinical gestalt to sort patients into groups based on how cri-
ment (START) triage system.3 tical their injuries are.
The process of START involves an initial sorting of patients
based on their ability to follow a command to leave the scene. Methods
Each patient is then assessed according to an algorithm that takes Disaster Lab Conceptualization
into account breathing, circulation (as measured by either the The Disaster Lab/Operation Central Shield project was conceived
presence of a radial pulse or measurement of finger capillary refill in September 2015 by a group of researchers at the University of
time), and ability to follow commands. A patient who is ambu- Massachusetts Medical School (Worcester, Massachusetts USA),
latory and follows commands is Green; a patient that is not and planning continued through September 2016 when the event
breathing is labeled Black; a patient who has an abnormality of was held and data were collected. The concept included a research
any of the above metrics is Red; and patients who have intact component designed to allow testing of multiple, innovative
respirations, circulation, and mentation but have other injuries are disaster-management techniques as well as a full-scale exercise
Yellow. This process is expected to take between 30 and 60 sec- (FSE) designed to assess the host region’s preparedness for a large-
onds per patient.3 scale MCI. Planning incorporated multiple stakeholders, such
The use of these criteria should identify patients that will as the area’s Central Medical Emergency Direction (CMED;
benefit most from the resources available, with the goal of Holden, Massachusetts USA), regionalized Emergency Medical
decreasing critical mortality (ie, the percentage of patients with Services (EMS), local fire departments, the Department of Public
survivable injuries who die).1,7 In addition, any algorithm should Health (DPH; Boston, Massachusetts USA), the local police
seek to minimize over-triage (the assignment of a well patient to department, and all hospitals in the city of Worcester, Massa-
an urgent category) and under-triage (the erroneous assignment of chusetts. The simulated MCI was designed as an “active-shooter”
an ill patient to a less urgent category). Over-triage puts patients at incident at a concert in a large, inner-city convention center.
risk by wasting resources that are needed for critical patients. Funding for the FSE was provided by the Central Massachusetts
Under-triage causes missed opportunities to use resources on Homeland Security Advisory Council (Worcester, Massachusetts
patients who need them urgently. Both types of error introduce USA) and conducted according to Homeland Security Exercise
inefficiency into the system and may result in increased critical and Evaluation Program (HSEEP; Washington, DC USA)
mortality.8 standards. Funding for the research aspect of the project was
Regardless of the triage methodology selected by an agency or provided by the University of Massachusetts Medical School.
government, it is important to ensure that the algorithm meets Study approval was obtained from the University of Massa-
some standard of utility and ease of use. Every modality necessi- chusetts Medical School academic Independent Review Board
tates initial and refresher training for providers and may have [IRB ID H00011322]. Table-top exercises and small-scale MCI
inherent limitations in its real-world use. As noted above, there is drills continued through August 2016, including input from local
also a time cost associated with using a formal triage modality with hospitals. Coordination with city planners regarding impact to the
published ranges between 30 and 60 seconds per patient.3,9 local community, traffic, schools, and the need for public messa-
Finally, many providers note that they do not always adhere to ging was undertaken. Additionally, coordination between the City
formal algorithms when applying the triage modalities in real- of Worcester, Massachusetts communications office, the area’s
world practice.10,11 office of the Mayor and City Manager, the DCU Convention
Despite most providers’ familiarity with the concept of triage, Center, the UMass Medical System, and the UMass Medical
there is a paucity of literature which demonstrates the effectiveness School was completed. The research exercise took place on the
of these methods in real-world or simulated situations.7 There has morning of September 20, 2016, followed by the afternoon
been research showing that focused teaching regarding a triage “Operation Central Shield” FSE.
system improves the rate of correctly triaging on written exams.12 “Victim” actors were recruited primarily to be participants in an
Computer algorithms have also been used to compare triage FSE being conducted to test the first response capability of the city
methods by retrospectively assigning patients according to chart and surrounding region. Those same volunteers agreed to parti-
review.4,6 In a retrospective review of the response to a 2003 train cipate in research studies being done in the morning before the
crash MCI, Kahn and colleagues found poor agreement between actual city-wide response drill. Actors, both men and women 18
START categories and outcome measures based upon hospital years old or older, were recruited from the community, area gov-
admission and modified Baxt criteria.13 They noted that while the ernment officials, local colleges, and the University of Massachu-
level of under-triage of Red patients was low, there was a sig- setts Medical School staff and their families by word of mouth and
nificant amount of over-triage. Another study compared the sen- paper fliers. One-hundred and forty-three people volunteered to
sitivity and specificity of a variety of triage methodologies and participate. Signed consent was obtained before any activity began.
found that many major modalities achieved sensitivities of First responders were recruited from local first responder agencies
between 82% and 85% with better specificities ranging from 86%- in the area through electronic email notifications. Purposefully,
96%.14 Both over-triage and under-triage have been observed in START was selected for evaluation as it is the MCI triage mod-
other studies, highlighting the imperfect and difficult nature of ality used by all EMS agencies in Massachusetts.16 Study partici-
MCI triage.11,15 pants were provided with lunch, lunch time entertainment from a
The researchers in this study are not aware of any studies that local band, and study tee shirts. In addition, each study participant
compare the use of one or more formal methodologies to a con- was given a stopwatch and instructed in its use prior to the study.
dition where responders triage patients without the use of an
established algorithm. The goal in this investigation was to com- Data Collection
pare the speed and accuracy of START and an “intuitive” triage Identical scenarios were run multiple times, each time using a
approach, in which a health care provider uses immediate, visual, different set of paramedic responders. Responders were

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 Hart, Nammour, Mangolds, et al 357

randomized to two groups: those instructed at the beginning of the

scenario to use START to assign triage categories, or those
instructed to simply use their intuition to assign a category to each
patient. Those responders in the START group were designated
the control group of this cluster randomized simulation. Responders
in both groups used standard Red/Yellow/Green/Black triage cards
to make the triage assignments. All participants were paramedics in
Massachusetts and were assumed to be knowledgeable regarding
the use of START triage as use of this modality is mandated in
MCIs by the Massachusetts Office of Emergency Medical Services
(OEMS; Boston, Massachusetts USA).16 Responders in the
“intuitive” groups were given no other instruction about the basis on
which to make decisions, other than: “Use your own intuition of
who should be assigned what triage category, but do not use
START triage.” Responders in the START group were instructed
to use the standard START methodology to assign a triage category
to each patient. Responders in both groups were told that the Hart © 2018 Prehospital and Disaster Medicine
simulation represented an MCI caused by an active shooter, and Figure 1. Scene Layout.
that dyes and props colored red should be considered blood. Care Note: The simulated active shooter was located on the stage
was taken to apply moulage to study volunteers in ways that would (box) in each scenario, leading to the higher triage categories
accurately depict the nature of their injuries, which ranged from of the simulated patients nearest this area. Higher acuity
severe, multi-system penetrating trauma to those who were (higher triage category) patients were grouped nearer to the
uninjured. stage. Arrows indicate the location of ingress of first
Volunteer victims were given information about their condition responders.
and whether or not they could respond to questions and ambulate,
as well as what their simulated respiratory rate should be. They The simulated scenario was an active shooter standing on the
were instructed to act in a similar manner during each trial and stage, so more-severe injuries were grouped near the stage while
were assigned specific locations within the simulation area to less injured patients tended to be further away from the stage.
ensure that they were “found” in exactly the same position for each Responders entered the scenes at analogous locations in both
trial. Victims were instructed to follow any commands given by scenarios (indicated by arrows in Figure 1). Two trials were run-
responders and to act out only injuries and vital signs indicated on ning simultaneously during the investigation but used a mirror
their victim identification cards. These cards matched moulage image patient distribution so that the responders were seeing
applied to their clothing and moulage applied to the rest of their exactly the same scene whether they were in Scenario A or Sce-
bodies as indicated. Responders were permitted, but not required, nario B. The patient distribution is presented in Figure 1. Not all
to look at the victim identification cards in each trial which showed victim positions were occupied as volunteers were limited, but in
their respiratory rate, capillary refill time, and level of alertness. both scenarios, victim distribution began near the simulated stages
With the exception of capillary refill, victims also acted out these (highlighted in boxes) and proceeded outward. This meant that
parameters. Victim presentations had been previously validated by the locations and numbers of victims in each category was similar
an independent group of three board certified Emergency Physi- for both Scenario A and Scenario B. Slight differences in total
cians who were also Board Certified in EMS practice through the numbers of victims and victim category distribution between the
American Board of Emergency Medicine (ABEM; East Lansing two scenarios was due to some volunteers spontaneously switching
Michigan USA). sides out of a desire to be near friends. Despite this, the overall
Data collection was performed by measuring the time taken distribution of patients was very similar, as can be seen in Table 1.
by each group of paramedics to assign each individual patient a Both intuitive triage and START protocols were run on each side,
triage category. This was accomplished by giving each “victim” a and data were aggregated for analysis to minimize any effect of
stopwatch, which they were then instructed to start at the slight differences between the two scenarios.
beginning of each iteration of the simulation and to stop the In addition to measuring the speed of triage category assign-
timer when they received a triage tag. Green patients were ment, the degree of accuracy of the triage results was measured.
instructed to stop their timers when they had walked to a pre- There was expected difficulty in measuring triage accuracy in a
designated data collection point away from the scene, if they were simulation due to variability in volunteer acting, moulage applica-
instructed to move by the responders. After all victims had been tion, and other “artificial” factors. Indeed, there are certain factors,
triaged in each trial, research assistants recorded the time on each such as the presence of large pools of rapidly accumulating blood,
stop watch and noted it according to the victim identification true respiratory distress, and others that, if present in real life, might
number. be expected to favor speed in an intuitive triage situation as these
A small number of individual victim triage times were not patients might naturally call attention more readily. Similarly,
recorded in the above fashion due to error, or they were illegible. patients with internal bleeding only or minimal visible injuries
For these values, researchers calculated a mean value for patients in might tend to favor more accurate triage by a method that deliber-
that category during that trial and used these imputed values to ately assesses vital signs such as capillary refill and respiratory rate.
perform subsequent statistical analysis. In all, such imputation was Finally, any “gold standard” assessment of the simulated vic-
performed for eight data points in the START trials and five data tims would, by necessity, rely on an existing triage algorithm such
points in the intuitive triage trials. as START to generate a pre-exercise “correct” triage category.

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 358 Intuitive vs Algorithmic Triage

Red Yellow Green Black Total

Scenario A 20 13 13 1 47

Scenario B 22 16 12 1 51
Hart © 2018 Prehospital and Disaster Medicine
Table 1. Victim Counts by Category

Total Comparisons (START Compared to Intuitive) Number of Agreements Percent Agreement

Scenario A 39 32 82

Scenario B 45 35 78

Total 84 67 80
Hart © 2018 Prehospital and Disaster Medicine
Table 2. Number of Instances of Triage Category Disagreement between START and Intuitive Triage Groups
Abbreviation: START, Simple Triage and Rapid Treatment.

Intuitive Triage Designation

START Designation Green Yellow Red Black

Green 0 2 2 0

Yellow 2 0 3 0

Red 0 6 0 2

Black 0 0 0 0
Hart © 2018 Prehospital and Disaster Medicine
Table 3. Instances of Disagreement between Triage Categories
Abbreviation: START, Simple Triage and Rapid Treatment.

This might skew the results for accuracy unfairly in favor of the that START assigned a “higher” or more urgent category than
START trials. intuitive triage, and vice-versa.
For these reasons, it was decided to compare the triage category
assignments for each patient between the two conditions (intuitive Results
triage and START) rather than comparing the decisions made by Comparison Analysis
the responders to a “correct” category. It was felt that this limited, There was a very high degree of agreement between triage cate-
to the greatest extent possible, any inaccuracy due to the artificiality gories in trials when comparing START and intuitive triage
of the simulation itself. In order to accomplish this, continuous groups. In Scenario A, there were 39 pair-wise comparisons pos-
video recordings were taken of the trials to review the triage category sible and 32 instances of agreement between START and intuitive
assigned to each patient in each trial. Each trial was filmed from two triage groups. In Scenario B, there were 45 pair-wise comparisons
perspectives, thus able to record patient triage categories as assigned possible and 35 instances of agreement between START and
by responders and indicated by the colored triage tags used. Most, intuitive triage (Table 2).
but not all, of the triage decisions were visible using the above Although there was a very high degree of agreement between
method. In cases where video evidence did not definitively show the two groups, it was also of interest to know whether one method
the triage colors, no assumptions were made and these data points (intuitive triage versus START triage) over- or under-estimated a
were not used in the comparison analysis. The researchers compared patient’s need for urgent transport. Both errors are known to occur
the triage decisions made by each group in each scenario (A and B) commonly in real-world situations and it is unrealistic to expect that
and performed a X2 analysis of the level of agreement between any triage modality that is sufficiently quick to allow assessment of a
START and intuitive triage groups in each scenario. large number of patients will not have some degree of inaccuracy.
Although speed data were collected for a total of five trials Therefore, to measure the rate of over- and under-triage in the study
(three START and two intuitive triage), comparison data for groups, a head-to-head comparison was performed to determine if
accuracy analysis were only available for four trials (two START one modality consistently over- or under-estimated patient severity in
and two intuitive triage) due to degraded video quality that made comparison to the other. Out of a total of 17 instances of disagree-
the analysis of the final START run impossible. This study also ment between the groups, the intuitive triage groups assigned a
measured percentage agreement between the triage categories higher category nine times (52%) - almost exactly one-half of the time
assigned in each trial, as well as calculated the percentage of time (Table 3).

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 Hart, Nammour, Mangolds, et al 359

START (Mean Seconds to Triage) [CI] Intuitive (Mean Seconds to Triage) [CI] P Value

All 106.57 [93.46-119.68] 72.18 [63.92-80.44] < .001

Combined Red/Yellow/Black 123.10 [108.53-137.67] 72.93 [64.31-81.55] < .001

Red 138.83 [120.04-157.62] 94.40 [84.49-104.31] < .001

Yellow 91.43 [73.36-109.48] 55.99 [43.73-68.25] .0018

Black 246.67[-20.35 to 513.69] 94.5 [-80.70 to 269.70] .192

Green 51.04 [41.60-60.48] 40.85 [28.26-53.44] .199

Hart © 2018 Prehospital and Disaster Medicine
Table 4. Mean Time to Triage
Abbreviation: START, Simple Triage and Rapid Treatment.

Hart © 2018 Prehospital and Disaster Medicine

Figure 2. Mean Time to Triage.
Abbreviation: START, Simple Triage and Rapid Treatment.

This result demonstrated that when disagreements occurred, the disagreement, the expected over-triage by one system was 8.5 epi-
groups were not significantly different in the number of times they sodes. Based upon this expected value, a Chi-squared analysis was
over- or under-triaged compared with each other. A Chi-squared performed and no significant difference between the two methodol-
analysis comparing the expected versus actual number of episodes of ogies was found (P = .971). This comports with the idea that over-
over-triage between the two groups was performed. For two equiva- and under-triage were observed essentially equally in the two triage
lently accurate triage systems, the number of over- and under-triage methodologies. This analysis was performed using Excel 2013 Data
would be equal when disagreements occurred. Given 17 episodes of Analysis (Microsoft Corp.; Redmond, Washington USA) package.

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 360 Intuitive vs Algorithmic Triage

The key results of this investigation were the average times the current standard of care triage methods, such as START. As
taken to perform triage. The analysis measured the total time that the injuries sustained by victims of MCIs are often time-sensitive,
each victim measured on his or her stopwatch before a triage the morbidity and mortality benefit of this could be significant.
category was assigned. This study compared START trials with The understandable reservation associated with such a triage
intuitive triage trials based on the mean time to triage for all method is concern over the accuracy of triage with such a rapid
patients and for patients within specific triage categories. This evaluation. However, given the agreement in triage categories
study also measured the average time to triage for the sickest found between intuitive triage and START in this study, it is
patients, and so compared average time to triage for the group of likely that this potential loss of accuracy would be minimal, and it
combined Red, Yellow, and Black categories. would be offset by the benefit due to the increased speed with
The times were compared using two-tailed, two sample T-tests which patients could be triaged and treatments begun.
assuming unequal variances and an expected difference in means
of zero. These analyses were performed using Excel 2013 Data
Limitations
Analysis package.
Although the results of this study suggest that intuitive triage
The concept of using intuitive triage was, as far as the
modalities may be effective and more time-efficient, significant
researchers could determine, new in the literature. Therefore, the
limitations of this study make further investigation necessary.
expected effect size of using this protocol compared to START
First, this study used a high-fidelity simulation, but the results of
triage was unknown. As an a priori power calculation requires an
studies in this type of environment always suffer from a reasonable
assumption of effect size, none was performed prior to this study.
doubt that real-world experience will track with that of responders
The results are reported in number of seconds to the assign-
during exercises. Although this is a difficult limitation to overcome
ment of a triage category. Intuitive triage was significantly faster
given the unpredictable nature of MCIs and the inherently dynamic
for all categories, except for Black and Green. It should be noted
environment of disasters, it is important to note. However, it should
that there were very few observations in the Black triage group, and
be considered that some elements of a real-life incident such as
that in both the START and intuitive groups, responders chose to
active bleeding and true respiratory distress might actually make
initially give a command for all patients who could walk to move
intuitive triage more rather than less applicable.
off of the field. This was done in the intuitive triage groups as well
Secondly, the simulated scenario was a particular type of fast
as the START groups, despite the intuitive triage groups not
moving MCI (ie, an active shooter) where wounds are more likely
being specifically instructed to do so. This may account for the
to be easily apparent and where time is extremely limited. It may
similarity of triage times between the two methodologies in the
well be that in other types of MCIs, a more traditional triage
Green category and may suggest that this type of mass sorting is an
methodology out-performs intuitive methodologies. This will only
ingrained part of responders’ intuitive approach to MCI triage.
be better understood through further study.
The results of this analysis are presented in Table 4 and
Third, this study compared triage decisions between the
Figure 2.
modalities as opposed to some measure of “gold standard” cor-
rectness. This was done intentionally to help ensure that the
Discussion
methods were compared fairly, but it is important in future work to
This study presents a comparison of the time required to triage
compare any new triage method to some objective standard of
patients on the scene of a simulated MCI using either an algo-
correctness in order to determine its test characteristics. This is just
rithmic triage modality such as START or what the authors have
one of many potentially useful avenues for further investigation.
referred to as “intuitive triage:” decision making based upon their
Finally, all of the responders who participated in this study
instinctive perception of how critical a patient is. The results were
were paramedics and so represented a higher level of training than
obtained during a high-fidelity simulation and demonstrated that
is present in many EMS systems around the country. It is possible
intuitive triage is much faster with seemingly little effect on triage
that their higher level of training allowed them to make more
accuracy. In fact, across all levels of patient criticality except dead
correct or insightful decisions than would be expected from pre-
(Black) and minimal (Green), there was a significant reduction in
hospital providers with less training.
time required to triage victims.
The recent trend in increased numbers of active-shooter inci-
dents and bombings make clear the need for response plans that Conclusions
take into account the time-critical nature of victims of these inci- This initial study of an intuitive triage method suggests that in
dents.14 Recent military and civilian experience has shown that certain types of MCIs, and with certain types of responders per-
interventions such as stopping bleeding and early transport to forming triage, much faster triage decisions can be made while
definitive surgical care are among the most effective ways to reduce maintaining accuracy in those decisions. Meanwhile, START and
critical mortality. Although the accepted time required to triage other triage algorithms have proven useful in a number of real-
each patient using traditional modalities is relatively short world applications, and any definitive conclusions about their
(30-60 seconds), this compounded over an MCI which includes utility should come only after further study is conducted into the
hundreds of victims could put many victims at risk of dying from potential of more intuitive and less algorithmic approaches. Still,
preventable causes while the triage process is on-going. this study does suggest that significant time could be saved using
The results of this study demonstrate the significant time such a method and clearly warrants further investigation to test the
benefit attainable by employing an intuitive triage method over results presented here.
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