Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_905_Библиотеки_им_академика_М_И_Перельмана.pdf
Surgeons andPilots: What Do
WeHave inCommon?
RifatLati
6
Introduction
Flying a plane (or riding in a plane for that matter) can be dangerous business, but still much
safer than a number of things we do regularly. In
fact, it is one the safest thing that we do. There
were 37.4 million ights in 2014, the highest
number ever, and this equates to more than
100,000 ights per day. Given the low number of
fatal crashes that year (1), you would statistically
have to y 5,342,857 times for every accident.
The average for 2010–2014 is lower, but still better than any previous ve-year period; one fatal
crash per 2,925,000 ights. That means a
0.000034% risk. You have never been less likely
to y on a plane that will crash and experience
fatalities [1]. Still the list of fatalities is extensive
and often high-prole [2]. Recent fatalities
include the AF Andrade Empreendimentos e
Participações Cessna 560XLS+ Citation Excel in
Guarujá, Brazil, where ve passengers and a pilot
were killed after crashing into a residential area
on 13 August 2014. On 10 August 2014, Sepahan
Airlines HESA IrAn 140, ight 217, near
Nardaran, Azerbaijan, ve crew members and 18
passengers were killed when the aircraft crashed
R. Lati (*)
Department of Surgery, The University of Arizona,
Tucson, AZ, USA
Tucson Medical Center, Department of Surgery,
Tucson, AZ, USA
e-mail: Lati@surgery.arizona.edu
shortly after takeoff. On 24 July 2014, Air Algerie
MD83, EC-LTV, ight AH5017, near Gossi,
Mali, crashed after the pilot contacted the control
tower to request a different route due to weather
conditions, killing six crew members and 119
passengers. Last few crashes have been mentioned in the introduction chapters.
Pilots and surgeons undergo intensive training. However, the question is do long and intensive trainings determine who will commit errors
and who will handle emergency situations effectively, in surgery or aviation. Numerous factors
play a part in how these situations are handled in
both elds. Some basic factors are similar and
include communication, technical skill, mental
state, and external distracting factors.
Once, in an interview, John O’Connell, a pilot
with more than 18,000hours of pilot in command
time, provided a brief vision of what a pilot may
have to encounter, and what that pilot perceives
he has to do in emergency situations. O’Connell
claims that there is a plan A, then a B, then a C
and D.More than one backup plan is necessary,
and it is good to have these plans mentally available during a time of crisis. Similarly, in complex
surgeries there must be a plan A, a plan B, and at
least a plan C, but in a ight, the public does not
see these plans. On the other hand, we surgeons
discuss these plans with a patient and family all
the time. The most important thing is to know the
basics of ying, down to a point where you don’t
even think about them, and to perform a surgery
plan A and not think about plan B and C, unless it
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
R. Lati (ed.), Surgical Decision-Making, https://doi.org/10.1007/978-3-031-67391-7_6
49
50
R. Lati
is really needed. But if you need them, you have
to play them down clearly. That way, in a time of
crisis, you address the crisis, and not the basic
activity of ying, or performing surgery in the
operating room. O’Connell states that the use of
checklists during specic situations is helpful.
For example, if the engine loses power, there is a
standard checklist that pilots go through in order
to systematically identify the problems that may
be causing the engine failure [3]. However, if the
patient has a cardiac arrest on the operating table,
while we surgeons do not have a written checklist
for that scenario hanging on the wall of the operating room, it is expected that we all know what
to do. That is, every surgeon should know what to
do, or call for help.
The safety of airlines is clearly multifactorial,
but both pilots and surgeons, as captain of the
“ship” play a major role and both are in charge of
the situation.
Performing surgery could be a dangerous and
complex process. The training that goes into
becoming a surgeon is even more intensive than
becoming a pilot. Surgeons typically have
between eleven to sixteen years of training,
including residency. The training is very complex
and it is not an easy process. Such training is necessary in order for the doctor to become a surgeon, an expert who is ready to deal with the
unexpected. Much like the scenario of a pilot
who does not have to think about the basics when
an emergency occurs, a surgeon cannot waste
time on thinking through basics of operating
when things get out of hand. It should be
effortless.
It takes many years of training before one can
independently take on a complex surgical case.
The training is so difcult that a recent anonymous survey of 371 categorical general surgery
residents and evaluation of 10-year attrition rates
for thirteen residency programs in the USA
revealed that 58.0% seriously considered leaving
training [4]. The most frequent reasons for wanting to leave were sleep deprivation on a specic
rotation (50.0%), an undesirable future lifestyle
(47.0%), and excessive work hours on a specic
rotation (41.4%). Factors most often cited that
kept residents from leaving were support from
family or signicant others (65.0%), support
from other residents (63.5%), and perception of
being better rested (58.9%). Interestingly, on univariate analysis, older age, female sex, postgraduate year, training in a university program, the
lack a faculty mentor, particularly in female residents, lack of female faculty mentors, and lack of
Alpha Omega Alpha status were associated with
serious thoughts of leaving surgical residency.
On multivariate analysis, only female sex was
signicantly associated with serious thoughts of
leaving residency (odds ratio, 1.2; P = 0.003),
while married male, and especially married male
with children were more satised in their residency program and did not think of leaving.
The authors [4] conclude that: “The training
of surgical residents is a long and arduous process that necessitates an immense investment of
time for the trainee and the faculty. As such, resident attrition is a tremendous loss for all involved
parties. In this multi-institutional survey of surgical residents, a majority seriously considered
leaving their training, and most had such
thoughts more than once. Given that prior investigations indicate that surgical residents who
think of quitting are more likely to subsequently
do so, the survey results herein are sobering. With
the increasing number of women entering surgical training, the fact that female sex predicted
thoughts of quitting in the present study is similarly concerning. Surgical training programs
should take heed of these ndings and work in a
cooperative fashion to address factors that
increase residents’ desire to leave surgical
residency.”
It is unclear what the true attrition rate is
among aircraft pilots, as the recent addition of
navigators of unmanned aircrafts has complicated things a bit. However, recent articles suggest that attrition of trainees from the aviation
program is a continuing concern for the
U.S.Navy, and each late-stage navy aviator training failure costs the taxpayer over $1000,000,
and ultimately results in decreased operational
readiness of the eet [5]. Over the past 20years,
the attrition rate of incoming aviation students
has been between 15–25%. As with surgical
trainees, attrition among pilot trainees occurs for
6 Surgeons andPilots: What Do WeHave inCommon?
51
a variety of reasons including medical problems.
However, most attritions result from academic or
ight performance failures or requests to be
dropped from the program. Naval aviation is a
highly stressful occupation requiring the ability
to respond quickly and appropriately in dangerous situations. While there is no measure of the
impact of psychological stress on attrition from
the program, it makes a clear contribution to academic/ight performance failures and drop out
request. Biological screening of potential aviators based on performance under psychological
stress could reduce all of the major contributing
factors of attrition, thus saving the Navy millions
of dollars.
There is a difference between how surgical
residents and pilots are selected. Potential aviators are currently selected using the Aviation
Selection Test Battery (ASTB). The ASTB is a
written test designed to evaluate math and verbal
skills, mechanical comprehension, aviation and
nautical information and spatial apperception.
The ASTB has a strong predictive validity
through primary ight training. While the ASTB
evaluates many skills necessary to aviation, and
is correlated with performance, it does not
account for the natural genetic variation in physiological stress response. Once selected by the
ASTB, all naval pilot trainees undergo water survival training in the Modular Egress Training
Simulator (METS) device, a highly demanding
and stressful test. In contrast, potential surgical
residents are interviewed, and have to demonstrate that they have done well in their past education, show dedication, but there is no physical
test. Actually, once I observed a chief resident
struggling while removing a gallbladder. I asked
him to see an optometrist, as I thought his glasses
were old and maybe he needed a new prescription. To my huge surprise, he admitted that he
had a depth perception problem that could not be
xed. Since then I have wondered why we do not
give a real comprehensive screening test for our
future surgeons.
Human performance under psychological
stress has been studied extensively, and it has
been primarily done psychometrically or using
reductionist biological methods such as blood
cortisol measurements [6]. Moreover, a study
published in 1999 that looked at the neuroendocrine responses among students suggested that
neuroendocrine reactions as a response to the
psychological workload of military ying could
be used for identifying stress tolerance in military pilots [7].
Both pilots and surgeons work under highly
stressful jobs, so identifying specic biomarkers
to predict who will make it through training, and
identify those who will not, would be quite useful. Such work would also provide potential biomarkers for screening humans for capability of
superior performance under stress. If this testing
is proved in the future to predict who will be able
to adapt better to high intensity situations, we
believe that such protocols should be extended to
future surgeons as well.
While there are a number of similarities
among pilots and surgeons, still there are some
other signicant differences between surgeons
and pilots with respect to public involvement.
Every pilot error is recorded, scrutinized, analyzed and made public; rarely are the errors of
surgeons made public. There is no recording of
the procedures, and, thus, it is impossible or very
difcult to replay the surgery and make it public.
Furthermore, because of privacy issues, only a
few major mistakes by surgeons ever make it to
the news.
Pilots andSurgeons:
TheDangerousJobs
Both pilots and surgeons have dangerous jobs;
these types of careers take the lives of other people in their hands while engaging in tasks that are
played out in dynamic, ever-changing contexts.
Paying attention to all available cues is of the
utmost importance. After all, people’s lives
depend on it! Like pilots, surgeons work in
dynamic environments, while taking responsibility for the lives of individuals and managing to
complete difcult tasks such as a pancreaticoduodenectomy, liver or lung resection, or takedown
of complex multiple stulas or managing a
patient major abdominal trauma after a high-
52
R. Lati
speed head-on collision in patient in severe shock
spiraling down, without knowing in advance
what you will nd in the abdomen. While these
and the countless other surgical procedures may
seem very difcult for non-surgeons or novice
and inexperienced trainees, and surgeons, the
well-trained surgeon can complete these procedures safely, but when a crisis arrives, things
change dramatically. Maybe as we surgeons have
a bit “more time” to address our crises, as our
operating room is not ying at 1000 km/hour.
Still, the environments of surgeons and pilots are
considered dynamic, meaning there is continual
change occurring within the environment. Often,
however, we do not have much time, as in patients
with cardiac stab or even blunt trauma in cardiac
tamponade.
When broken down by steps, work within
dynamic environments can be tted into three
major categories. First, the pilot or surgeon must
continually monitor and assess the situation.
While this is the rst step in the process, it is also
continual. The pilot or surgeon has to assess the
situation with each development in order to process how to respond and which step to take next.
He or she must then take appropriate reactions
based on assessment. Once appropriate action is
taken, evaluation of results must be made. The
cycle then repeats itself [8, 9]. These jobs are
intensely stressful, not only because people’s
lives are dependent upon decisions that are made,
but there is no “down-time” while performing
these jobs. A surgeon can’t go take a break during
a long and intense surgery. A pilot can’t stop ying a plane if he doesn’t feel well. Additionally, a
key aspect to functioning successfully in complex dynamic environments is the ability not only
to observe and seek information, but to understand what that information means in the larger
context of a task goal [10]. Moreover, an ability
to then anticipate events in that environment
leads to better prediction and understanding of
future events. The cognitive components of these
processes are of interest to researchers and will
briey be discussed in this chapter. While these
cognitive components are of interest, a major
goal of this chapter is to establish what may be
occurring when a surgeon or pilot seemingly
makes a “gut-level” decision. There is a whole
host of other factors that the operator is not aware
of, such as the integration of the information they
have learned through training and experience.
This phenomenon can be called situational
awareness, sense-making, or unconscious processing of environmental cues. Regardless of the
term used, the concept has been reviewed in a
number of ways, particularly in the literature on
the abilities of pilots [10–13].
Situational Awareness
andCommon Sense-Making
Situational Awareness is a concept that has been
studied extensively for pilots and can be applied
to surgeons in the operating room. Military strategists have applied this concept to operating aircraft, ships, and in emergency military situations.
As described in chapter two of this book, situational awareness can briey be described as “the
perception of elements within a volume of time
and space, the comprehension of their meaning,
and the projection of their status in the near
future [9].” Numerous studies looking at the
effects of situational awareness in virtual and real
environments among military personnel have
been conducted [9]. Few studies have been conducted that look at how situational awareness can
be applied in the medical eld.
Of the few studies that investigate situational
awareness (SA) in the medical eld, either communication among surgical team members or the
usefulness of the concept of situational awareness has gained most attention; these aspects are
also termed non-technical skills. Postgraduate
training in the medical eld is extensive, but
especially in surgical disciplines. With this postgraduate training, several technical skills are
acquired from how to approach and examine the
patient and identifying problems that need an
intervention, to highly technical procedures for
various operations. However, non-technical skills
are somewhat individually-based, and not every
surgeon is trained for the same, although the
6 Surgeons andPilots: What Do WeHave inCommon?
53
basics are fairly similar. These skills are just as
valuable as technical ones, and are a common
subject of investigation for surgical never-events.
As described earlier in the book, surgical never
events are events that include operating on the
wrong patient, performing the incorrect surgery,
operating on the wrong limb, etc. These errors
are substantially high and are easily remedied if
the proper precautions are taken [14]. Specically,
the use of non-technical skills, such as communication and organization, is required in order to
prevent surgical never events.
The concept of situational awareness has been
investigated in order to prevent these forms of
errors. For example, Gaba etal. discusses potential application of the concept among anesthesiologists [14]. Flin etal. make a case for applying
decision-making analysis concepts (i.e., naturalistic decision-making) in a two-step process that
includes: assessing and diagnosing the situation,
then using one of four strategies to make a decision [15]. These strategies are selected based on a
continuum of urgency, and include intuitive recognition, rule-based, analytical, and creative
decision-making. When the need to make a decision is urgent, intuitive recognition decisionmaking is used, whereas when the need to make
a decision is not urgent, creative decision-making
is used [15]. For example, creative decisionmaking requires more time and less urgency. It
appears that there is a blend of intuitive recognition decision-making and creative decisionmaking during surgery.
According to Mica Endsley, a pioneer in the
eld of SA, there are different levels of SA [11,
12]. At the lowest level of SA, a person needs to
perceive relevant information (Level 1 SA).
Integrating various pieces of information, while
keeping the overall objective of the task in mind,
allows the individual to form an understanding of
the meaning of that information within context,
forming Level 2 SA.Based on this understanding, future events can then be predicted (Level 3),
allowing for timely and effective decisionmaking. Several processing mechanisms have
been hypothesized to be related to SA, including
attention and working memory limitations, atten-
tion distribution, current goals, mental models,
schemata, and automaticity [10–12]. In addition
to characteristics of individuals, the design of a
system, for example, how patient information
ows to the surgeon prior to surgery, and the
team environment can affect SA.
Situation Awareness, Perception, Comprehension, Projection
The three main factors that drive or underlie SA
are perception, comprehension, and projection
[16–19]. These can easily be mapped onto the
levels described by Endsley. These concepts
allow for awareness to be parceled out into tractable portions for further understanding. One of
the cognitive processes associated with SA is that
of working memory (WM). Personally, from very
busy surgical practice, I took a leave of absence
from surgery for 18months, while serving as the
Minister of Health for the Republic of Kosova
and taking a few months off after that. When I
returned to operating, I performed as the rst
case, a major complex abdominal wall reconstruction, and was fascinated how I my working
memory took place immediately, and I had no
problems asking for the instruments that I had not
even thought about for 18months. I guess there is
a reason why we say “It’s like riding a bike” to
mean that that once you learn how to do something, you never forget it. Working memory can
be dened as the system that actively holds multiple pieces of transitory information in the mind,
where they can be manipulated. Working memory includes subsystems that store and manipulate visual images or verbal information, as well
as a central executive that coordinates the subsystems. It includes visual representation of the possible moves, and awareness of the ow of
information into and out of memory, all stored
for a limited amount of time. Working memory
tasks require monitoring, which is a component
of SA, as part of completing goal-directed actions
in dynamic environments. The cognitive processes needed to achieve this include the executive and attention control of short-term memory,
54
R. Lati
which permit interim integration, processing, disposal, and retrieval of information. These processes are sensitive to age: working memory is
associated with cognitive development, and
research shows that its capacity tends to decline
with old age. In addition, neurological studies
demonstrate a link between working memory and
learning and attention, as well as being an underlying component of SA [17].
Conclusion
Both pilots and surgeons have to make serious
decisions that are time dependent and may have
serious consequences. While the pilot is supported
by the most sophisticated technologies of the ying machine, which now a days have full control
on their own, the surgeon has to make decisions
that are highly dependent on his or her experience, knowledge, and often this decision is gut
based. Overall, these decisions are made in highly
dynamic and changing environments. Awareness of
the individual state of the surgeon and pilot is crucial, together with awareness of the operating environment, such as communication dynamics among
the teams. Not being aware of certain subtleties in
communication may be detrimental to both surgical and piloting outcomes. Additionally, extensive
training will allow for a surgeon and a pilot to be
prepared for unexpected events. Checklists, while
possibly viewed as something to be used by novices only, have been shown to be helpful with pilots
and surgeons [20, 21, 22]. Finally, there is much
to learn regarding how and why individuals make
decisions, particularly decisions that appear to be
gut-level or unconscious. The research in this eld
is valuable and informative for professions that
make decisions in dynamic environments that will
affect the lives of other individuals.
Still major errors or so called “human errors”
are attributed to major catastrophes in aviation,
both commercial and private, while in surgery we
attribute “technical errors”, “error in judgment”
to surgeons, and it is not uncommon, to mix with
“the patients’ disease” as a major attribution to
bad outcome. Imagine, if the pilots y really old
airplanes, with no updated software or hardware,
like surgeons operating in a geriatric population
which has, in addition to being old, several
comorbidities. And we surgeons do this day in
and day out.
References
1. Garfors G. Is it safe to y? Globetrotting Galore.
2015. Retrieved October 20, 2015, from http://www.
garfors.com/2015/03/is- it- safe- to- y- dangerous.html
2. ABC News. In wake of emergency landings, pilot
simulates situations. 2014. Retrieved October 20,
2015, from http://www.abc- 7.com/story/26293414/
in- wake- of- emergency- landings- pilot- simulatessituations#.VibA6H6rSUl
3. Federal Aviation Administration (FAA). Federal
Aviation Administration (FAA). 2015. Retrieved
October 20, 2015, from http://www.faa.gov/
4. Gifford E, Galante J, Kaji AH, etal. Factors associated
with general surgery residents’ desire to leave residency programs: a multi-institutional study. JAMA
Surg. 2014;149(9):948–53. https://doi.org/10.1001/
jamasurg.2014.935.
5. Cooksey AM, Momen N, Stocker R, Burgess
SC. Identifying blood biomarkers and physiological processes that distinguish humans with superior
performance under psychological stress. PLoS One.
2009;4(12):e8371. https://doi.org/10.1371/journal.
pone.0008371.
6. Schedlowski M, Wiechert D, Wagner TO, Tewes
U. Acute psychological stress increases plasma
levels of cortisol, prolactin and TSH. Life Sci.
1992;50:1201–12051.
7. Leino TK, Leppäluoto J, Ruokonen A, Kuronen
P. Neuroendocrine responses to psychological workload of instrument ying in student pilots. Aviat Space
Environ Med. 1999;70(6):565–70.
8. Endsley MR. Towards a theory of situation awareness in dynamic environments. Hum Factors.
1995;37:32–64.
9. Endsley MR.A survey of situation awareness requirements in air-to-air combat ghters. Int J Aviat Psychol.
1993;3:157–68.
10. Endsley MR.Measurement of situation awareness in
dynamic systems. Hum Factors. 1995;37:65–84.
11. Endsley MR.The application of human factors to the
development of expert systems for advanced cockpits. In: Proceedings of the 7th international symposium on aviation psychology. Columbus: Ohio State
University; 1987. p.167–71.
12. Durso FT, Sethumadhavan A. Situation awareness:
understanding dynamic environments. Hum Fact J
Hum Fact Ergonom Soc. 2008;50:442–50. https://doi.
org/10.1518/001872008X288448.
6 Surgeons andPilots: What Do WeHave inCommon?
55
13. Mehtsun WT, etal. Surgical never events in the United
States. Surgery. 2013;153(4):465–72.
14. Gaba DM, Howard SK, Small SD.Situation awareness in anesthesiology. Hum Fact J Hum Fact
Ergonom Soc. 1995;37:20–33.
15. Flin R, Youngson G, Yule S. How do surgeons
make intraoperative decisions? Qual Saf Health
Care. 2007;16:235–9. https://doi.org/10.1136/
qshc.2006.020743.
16. Gutzwiller RS, Clegg BA.The role of working memory in levels of situation awareness. J Cogn Eng Decis
Making. 2013;7(2):141–54.
17. Durso FT, Sethumadhavan A. Situation awareness:
understanding dynamic environments. Hum Fact J
Hum Fact Ergonom Soc. 2008;50:44.
18. Bedny G, Meister D.Theory of activity and situation
awareness. Int J Cogn Ergon. 1999;3:63–72.
19. Smith D.Introduction to aeronautical decision making. Retrieved 08 October 2009 from the World Wide
Web: ADM; 2002.
20. Aircare. An aviators guide to good decision making.
Welligton: Aircareå; 2006.
21. Gawande A. The checklist manifesto: how to get
things right. NewYork: Metropolitan Books, Henry
Holt and Company, LLC; 2009.
22. Anwer M, Manzoor S, Muneer N, Qureshi S.
Compliance and effectiveness of WHO surgical safety check list: A JPMC Audit. Pak J Med
Sci. 2016;32(4):831–5. https://doi.org/10.12669/
pjms.324.9884. PMID: 27648023; PMCID:
PMC5017086.
Planning andPreparing
fortheOperation: TheRole
ofArticial Intelligence inModern
Surgery
J.EstebanFoianini andGennaBeattie
7
Introduction
As surgeons, we have to make surgical decisions
based on multiple variables. Often, these decisions are not based on evidence. Irrespective of
how one makes the decisions, it will affect the
course of the surgical intervention and may
impact the patient’s eventual outcome.
As we plan for an operation, surgeons have
historically used hypothetical reasoning based on
current literature, surgical training, mentors, and
previous experience. This reasoning is called
clinical “gestalt” and is the method by which
many clinical decisions are still made.
In the era of evidenced-based surgery and datadriven results, there has been an attempt to generate predictive models to plan surgical procedures
and predict outcomes in our patients. However,
complex and cumbersome decision trees or unreliable algorithms have hindered the application of
these tools in everyday surgical practice. Survival
data is typically studied using linear models [1, 2].
Unfortunately, we know that surgical complications are non-linear [3].
J. E. Foianini (*)
Surgeon and Medical Director, Clinica Foianini,
Santa Cruz, Bolivia
e-mail: efoianini@clinicafoianini.com
G. Beattie
Clinical Fellow (PGY-9), Trauma & Acute Care
Surgery, University of California San Francisco,
San Francisco, CA, USA
e-mail: genna.beattie@ucsf.edu
Articial Intelligence (AI) and machine learning have begun to revolutionize all aspects of our
lives, and most recently, there has been increased
interest in its role in medicine. One of the advantages of AI is its non-linear properties, which
allow it to perceive relationships that are not
readily apparent. AI is particularly suited to analyzing large datasets, computing complex interactions, identifying hidden patterns, and
generating actionable predictions in clinical settings [4]. At present, AI’s role in interpreting
imaging studies has been one of its rst incursions into the medical eld. However, AI is
poised to alter how we diagnose and treat patients,
and it will become prevalent in our daily and professional lives shortly.
With the ready availability of electronic medical records (EMR) and storage of immense
amounts of health data, it seems logical that AI
should integrate with these systems to obtain the
data and inform the provider of potential risks
and outcomes. Ideally, the EMR would notify the
provider of possible adverse outcomes, calculate
risks when the patient’s EMR is accessed, and
send alerts for critical events to ensure a prompt
and adequate response by the healthcare
provider.
Surgeons have been taught to rely on current
evidence, past clinical experiences, mentor teachings, and institutional protocols. These experiences are critical to surgical decision-making but
also introduce a degree of surgical bias. AI will
not remove all of these potential biases, but it can
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
R. Lati (ed.), Surgical Decision-Making, https://doi.org/10.1007/978-3-031-67391-7_7
57
58
J. E. Foianini and G. Beattie
collect a large amount of data and variables and
nd patterns that can assist us in predicting outcomes and dening treatment.
Since AI is an emerging technology, its application within surgery is still limited. As of this
writing, it is clear that AI can potentially allow
for risk stratication in surgical treatments or
procedures and their associated complications. It
may also serve to predict treatment outcomes,
morbidity, and survival. AI is altering how we
look at and process data, which will directly
impact how we conduct medical research in the
future.
Furthermore, models are being developed that
will allow us to predict subgroups of patients at a
higher risk for complications. Then, we can tailor
treatment to mitigate the possibility of specic
complications. In this chapter, we will review
several applications of AI in surgical and clinical
practice. As it stands currently, knowing fully
that the role of AI will expand dramatically in
every aspect of modern surgery.
Denitions
Articial Intelligence refers to computer systems
capable of performing complex tasks that historically only humans could do, such as reasoning,
making decisions, or solving problems [5]. It
emulates human cognition and can learn from
training examples to predict future events [6].
Three common terms are associated with AI:
machine learning, neural networks, and deep
learning. Machine learning (ML) is a branch of
AI and computer science where machines can
recognize patterns and learn from their experiences without being explicitly programmed
[7–9].
ML is the most widely applied arm of AI in
medicine. ML is particularly useful in settings
where signals and data are produced faster than
the human brain can interpret and in identifying
subtle patterns in large datasets [10]. It can identify patterns imperceptible to humans performing
manual analysis as it allows for more indirect and
complex non-linear relationships [11].
Neural networks are a sub-eld of machine
learning, and deep learning (DL) is a sub-eld of
neural networks [12]. Neural networks process
signals in layers of single computational units.
Deep learning networks are neural networks
composed of many layers and can learn more
complex patterns [11].
XGBoost, which stands for Extreme Gradient
Boosting, is a scalable, distributed gradientboosted tree machine learning library. It is the
leading machine-learning library for regression,
classication, and ranking problems [13].
The Area Under the Curve (AUC) measures
the accuracy of a quantitative diagnostic test [14].
It has critical applications in various elds, such
as statistics, machine learning, and analyzing
real-life data [15]. The higher the AUC, the better
the model’s performance at distinguishing
between the positive and negative classes.
Augmented Reality During Surgery
AI can provide augmented reality (AR) during
surgery. The technology superimposes images
onto structures, allowing it to highlight critical
anatomical structures and point out potential pitfalls. In this sense, it assists the surgeon but is not
poised to replace the surgeon during the procedure. A typical example of AR is during laparoscopic cholecystectomy, as it can identify areas
of potential harm or injury to vital structures. A
recent publication described a DL model that
provided real-time intraoperative guidance. This
model identied safe and dangerous zones of dissection during laparoscopic cholecystectomy
[16]. These systems intend to provide real-time
guidance and minimize the risk of adverse events.
The incorporation of AR during laparoscopic
cholecystectomy could potentially lead to a
reduction in the risk of bile duct injury during
these procedures in the future.
Another example of AR is during oncological
surgery for a liver tumor. The AR allows the surgeon to visualize the tumor and determine its
relationship to major intra-parenchymal vascular
structures in real time [17]. In the future, AR
7 Planning andPreparing fortheOperation: TheRole ofArticial Intelligence inModern Surgery
59
should become widespread in modern operating
theaters and will probably be applied to most
minimally invasive procedures.
Overall Surgical Complications
AI will signicantly impact how we analyze and
predict surgical complications. Surgical complications occur in as many as 34% of procedures.
Importantly, underestimating complication risks
can lead to the under-triage of high-risk patients,
impacting their clinical outcomes [18, 19].
Several models have been developed to determine the risk of postoperative complications.
Accurate predictions of complications are essential for precise clinical decision-making, shared
decisions between the patient and the surgeon,
allocation of resources, quality benchmarking,
and planned postoperative disposition (general
ward versus intensive care unit). Most current
models suffer from suboptimal performance, limitations of manual data entry, and a lack of clinical workow integration [19].
Surgical Risk Models
The American College ofSurgeons
Surgical Risk Calculator (ACS-SRC)
One of the most utilized risk calculators is the
American College of Surgeons Surgical Risk
Calculator (ACS-SRC), which uses data from the
American College of Surgeons National Surgical
Quality Improvement Program (ACS-NSQIP).
The ACS-SRC risk calculator can be assessed at
https://riskcalculator.facs.org/RiskCalculator/.
ACS-SRC is an excellent tool widely used to
inform treatment and support clinical decisions
[20]. One of its limitations is that it is an online
platform requiring manual data entry, which is
not integrated into the clinical workow. The
report can be emailed to the clinician or printed
as a PDF (Fig.7.1).
Images are obtained from the ACS-SCR calculator, which is a web-based platform. The latest version of the ACS-SCR provides the
following quote: “The Risk Calculator’s riskestimating methodology has now transitioned
from regression to machine learning. This change
in methodology will improve the calculator’s
already excellent accuracy, though differences in
estimated risk should not be large.” [21]
The Predictive OpTimal Trees
inEmergency Surgery Risk Calculator
(POTTER)
The Predictive OpTimal Trees in Emergency
Surgery Risk Calculator (POTTER) was introduced in 2018. The ACS-SRC is tailored to elective surgical patients, while the POTTER
calculator is geared towards emergency surgery.
This ML risk calculator for emergency surgery is
available for iOS and Android smartphones at no
expense. The developers intend to integrate the
calculator into the EMR in the future.
The calculator predicts 30-day postoperative
mortality, morbidity, and each one of the 18 individual postoperative complications of the ACSNSQIP, such as renal failure, respiratory failure,
myocardial infarction, or deep vein thrombosis.
With regard to 30-day postoperative morbidity,
the c-statistic of the POTTER algorithms was the
highest at 0.8414, outperforming the American
Society of Anesthesiology (ASA) (0.7842),
Emergency Surgery Score (ESS) (0.7768), and
the ACS-SRC (0.8063). The POTTER calculator
predicted the occurrence of individual 30-day
postoperative complications with a moderate to
extremely high accuracy (c-statistic range from
0.7358 to 0.9338). It performed best in predicting
postoperative septic shock (c-statistic 0.9338),
postoperative ventilator dependence for longer
than 48 hours (0.9254), and postoperative renal
failure (0.9126) [3]. In a follow-up article, the
lead authors compared the POTTER calculator
with surgeon gestalt. The POTTER calculator
outperformed surgeon gestalt in predicting postoperative mortality and outcomes in Emergency
General Surgery cases. Surgeon-predicted estimates were mostly higher and signicantly more
dispersed than POTTER estimates (Fig. 7.2)
[22].