Clary Foote M.D., Mohit Bhandari M.D., Ph.D., F.R.C.S.C. (auth.), Manish K. Sethi, A. Alex Jahangir, William T. Obremskey (eds.) Orthopedic Traumatology An Evidence Based Approach Springer Verlag New

Prévia do material em texto

Orthopedic Traumatology
 
Manish K. Sethi ● A. Alex Jahangir
William T. Obremskey
Editors
Mohit Bhandari ● Mitchel B. Harris
Michael D. McKee ● Steven A. Olson 
Paul Tornetta, III ● Roy W. Sanders 
Andrew H. Schmidt
Section Editors
Orthopedic Traumatology
An Evidence-Based Approach
Editors
Manish K. Sethi
Department of Orthopedic Surgery 
and Rehabilitation
Vanderbilt University Medical Center
Nashville, TN, USA
William T. Obremskey
Department of Orthopedic Surgery 
and Rehabilitation
Vanderbilt University Medical Center
Nashville, TN, USA
A. Alex Jahangir
Department of Orthopedic Surgery 
and Rehabilitation
Vanderbilt University Medical Center
Nashville, TN, USA
ISBN 978-1-4614-3510-5 ISBN 978-1-4614-3511-2 (eBook)
DOI 10.1007/978-1-4614-3511-2
Springer New York Heidelberg Dordrecht London
Library of Congress Control Number: 2012940415
© Springer Science+Business Media New York 2013
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of 
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v
 Orthopedic surgeons who manage the injured patient have always sought the best 
information on which to make treatment decisions. In the past, this has generally 
consisted of large textbooks with a comprehensive listing of all articles on a particu-
lar injury, with an author’s expert opinion and treatment recommendations synthe-
sizing this information. With the evolution of higher quality clinical research 
methods, orthopedic trauma surgeons have been in the lead and the paradigm has 
shifted. Because levels of evidence are now routinely inserted into the medical 
 literature and has scienti fi c presentations, the desire to have the strongest case for 
treatment decisions has increased. As the number of Level I and Level II studies has 
proliferated in the orthopedic trauma literature, the need for aggregation of this 
information into easily accessible formats has escalated. This need is speci fi cally for 
surgeons treating patients at the point of care. 
 Drs. Sethi, Jahangir, and Obremskey have taken the next step in the synthesis of 
higher levels of evidence for the practicing orthopedic surgeon. The fi eld of ortho-
pedic trauma surgery is wonderfully diverse in the types and locations of skeletal 
and soft tissue injury. This is one of the attractions of a career in orthopedic trauma-
tology: the fact that while some injuries are common and managed frequently, oth-
ers are extremely rare. The authors have taken the practical approach of taking the 
most commonly seen orthopedic injures, in which the most comprehensive evi-
dence base exists, and aggregating the information in a useful format. They have 
organized the chapters around common clinical scenarios taken from real-life expe-
rience. The case scenarios are then followed by a synthesis of the best clinical litera-
ture focusing on Level I and Level II studies. The scienti fi c technique of meta-analysis 
and the structured literature review are strictly employed to provide the reader with 
the best recommendations for management of an individual injury. Those principles 
of literature synthesis using scienti fi c methodology are explained in an introductory 
chapter to enhance the utility of the individual chapters. 
 The progression of clinical research and orthopedic traumatology has de fi nitely 
moved towards collaborative focused research using multicenter teams. Each year 
the number and quality of clinical research articles improves. This book is a wonder-
ful fi rst step in synthesizing this information into a format useful to the individual 
 Foreword 
vi Foreword
surgeon working with the patient and their family in making treatment decisions. 
As the clinical research and datasets expand, the work will need to expand. I expect 
that this work will be frequently revised on a regular basis to help all of us in the 
orthopedic community to deliver the best care for our patients. 
 I enthusiastically recommend this book to orthopedic surgeons everywhere.
Marc Swiontkowski 
vii
Part I Evidence-Based Medicine in Orthopedic Trauma Surgery
Mohit Bhandari
 1 Introduction to Evidence-Based Medicine ............................................ 3
Clary Foote and Mohit Bhandari
Part II Spine Trauma
Mitchel B. Harris
 2 Cervical Spine Clearance ....................................................................... 23
Andrew K. Simpson and Mitchel B. Harris
 3 Cervical Spine Fracture Dislocation ..................................................... 41
Kevin R. O’Neill, Jesse E. Bible, and Clinton James Devin
 4 Lumbar Burst Fractures ........................................................................ 55
Robert Greenleaf and Mitchel B. Harris
Part III Upper Extremity Trauma
Michael D. McKee
 5 Scapula Fractures ................................................................................... 71
Peter A. Cole and Brian W. Hill
 6 Clavicle Fractures ................................................................................... 87
Christopher R. Geddes and Michael D. McKee
 7 Proximal Humerus Fracture .................................................................. 103
Daniel J. Stinner, Philipp N. Streubel, and William T. Obremskey
 8 Humeral Shaft Fractures........................................................................ 129
Bill Ristevski and Jeremy Hall
 Contents
viii Contents
 9 Distal Humerus Fractures ...................................................................... 141
Andrew Jawa and David Ring
10 Distal Radius Fractures .......................................................................... 151
Cameron T. Atkinson, Philipp N. Streubel, and Jeffry Watson
Part IV Acetabular, Hip and Pelvic Trauma
Steven A. Olson
11 Acetabular Fractures in the Elderly ...................................................... 169
John C. Weinlein, Edward A. Perez, Matthew I. Rudloff, 
and James L. Guyton
12 Pelvic Ring Injury I................................................................................. 185
Damien G. Billow and Steven A. Olson
13Pelvic Ring Injury II ............................................................................... 195
Matthew D. Karam and David C. Templemen
14 Femoral Neck Fractures in the Elderly ................................................. 207
Dave Polga and Robert T. Trousdale
15 Intertrochanteric Femur Fractures ....................................................... 219
Hassan R. Mir and George J. Haidukewych
Part V Lower Extremity Trauma 
Paul Tornetta, III
16 Diaphyseal Femur Fractures .................................................................. 235
Manish K. Sethi, Kyle Judd, A. Alex Jahangir, 
and William T. Obremskey
17 Distal Femur Fractures........................................................................... 247
A. Alex Jahangir and William M. Ricci
18 Knee Dislocations .................................................................................... 261
Samuel N. Crosby Jr., Manish K. Sethi, and William T. Obremskey
19 Tibial Plateau Fractures ......................................................................... 277
Jodi Siegel and Paul Tornetta III
20 Closed Diaphyseal Tibia Fractures........................................................ 291
Marlis T. Sabo and David W. Sanders
21 Open Diaphyseal Tibia Fractures .......................................................... 303
Scott P. Ryan, Christina L. Boulton, and Robert V. O’Toole
ixContents
Part VI Foot and Ankle Trauma
Roy W. Sanders
22 Pilon Fractures ........................................................................................ 323
David P. Barei
23 Ankle Fractures ....................................................................................... 345
Conor P. Kleweno and Edward K. Rodriguez
24 Calcaneus Fractures ............................................................................... 359
Theo Tosounidis and Richard Buckley
25 Talus Fractures ........................................................................................ 373
Hassan R. Mir and Roy W. Sanders
Part VII Polytrauma, Infection, and Perioperative Management 
of the Orthopedic Trauma Patient
Andrew H. Schmidt
26 Damage Control ...................................................................................... 389
Laurence B. Kempton and Michael J. Bosse
27 DVT Prophylaxis in Orthopedic Trauma ............................................. 405
Keith D. Baldwin, Surena Namdari, and Samir Mehta
28 The Infected Tibial Nail .......................................................................... 417
Megan A. Brady and Brendan M. Patterson
29 Perioperative Optimization in Orthopedic Trauma ............................ 431
Clifford Bowens Jr. and Jesse M. Ehrenfeld
Index ................................................................................................................. 445 
 
xi
 Cameron T. Atkinson , M.D. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center , Nashville , TN , USA 
 Keith D. Baldwin , M.D., M.S.P.T., M.P.H. Orthopedic Surgery , Hospital of the 
University of Pennsylvania , Philadelphia , PA , USA 
 David P. Barei , M.D., F.R.C.S.(C) Department of Orthopedics , Harborview 
Medical Center, University of Washington , Seattle , WA , USA 
 Mohit Bhandari , M.D., Ph.D., F.R.C.S.C. Division of Orthopedic Surgery , 
 McMaster University , Hamilton , ON , Canada 
 Jesse E. Bible , M.D., M.H.S. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center , Nashville , TN , USA 
 Damien G. Billow , M.D. Department of Orthopedic Surgery and Rehabilitation, 
Vanderbilt University Medical Center , Nashville , TN , USA 
 Michael J. Bosse , M.D. Orthopedic Surgery , Carolinas Medical Center, Charlotte , 
 NC , USA 
 Christina L. Boulton , M.D. Department of Orthopedic Traumatology , R Adams 
Cowley Shock Trauma Center , Baltimore , MD , USA 
 Clifford Bowens Jr., M.D. Orthopedic Anesthesia, Department of Anesthesiology , 
 Vanderbilt University School of Medicine , Nashville , TN , USA 
 Megan A. Brady , M.D. Department of Orthopedic Surgery , MetroHealth , 
 Cleveland , OH , USA 
 Richard Buckley , M.D., F.R.C.S. Department of Surgery , Foothills Hospital, 
University of Calgary , Calgary , AB , Canada 
 Peter A. Cole , M.D. Department of Orthopedic Surgery , Regions Hospital, 
University of Minnesota , St. Paul , MN , USA 
 Contributors 
xii Contributors
 Samuel N. Crosby Jr. M.D. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center , Nashville , TN , USA 
 Clinton James Devin , M.D. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center , Nashville , TN , USA 
 Jesse M. Ehrenfeld , M.D., M.P.H. Biomedical Informatics, Department of 
Anesthesiology, Vanderbilt University School of Medicine , Nashville , TN , USA 
 Clary Foote , M.D. McMaster University , Hamilton , ON , Canada 
 Christopher R. Geddes , M.D., M.Sc. Division of Orthopedic Surgery , 
 Department of Surgery, University of Toronto, St. Michael’s Hospital , Toronto , ON , 
 Canada 
 Robert Greenleaf , M.D. Reconstructive Orthopedics , Lumberton , NJ , USA 
 James L. Guyton , M.D. Department of Orthopedics Surgery , Regional Medical 
 Center-Memphis, Methodist Germantown Hospital, University of Tennessee/ 
Campbell Clinic , Germantown , TN , USA 
 George J. Haidukewych , M.D. Orlando Health Level One Orthopedics , Orlando , 
 FL , USA 
 Jeremy Hall , M.D. Department of Surgery/Orthopedic Surgery , St. Michael’s 
Hospital , Toronto , ON , Canada 
 Mitchel B. Harris , M.D., F.A.C.S. Orthopedic Trauma, Department of Orthopedic 
Surgery , Harvard Medical School, Brigham and Women’s Hospital , Boston , MA , 
 USA 
 Brian W. Hill , M.D. Department of Orthopedic Surgery , Regions Hospital, 
University of Minnesota , St. Paul , MN , USA 
 A. Alex Jahangir , M.D. Department of Orthopedic Surgery and Rehabilitation , 
 Vanderbilt University Medical Center , Nashville , TN , USA 
 Andrew Jawa , M.D. Department of Orthopedic Surgery , Boston University 
Medical Center , Boston , MA , USA 
 Kyle Judd , M.D. Department of Orthopedic Surgery and Rehabilitation , Vanderbilt 
University Medical Center , Nashville , TN , USA 
 Matthew D. Karam , M.D. Department of Orthopedics and Rehabilitation , 
 University of Iowa Hospitals , Iowa City , IA , USA 
 Laurence B. Kempton , M.D. Orthopedic Surgery , Carolinas Medical Center , 
 Charlotte , NC , USA 
 Conor P. Kleweno , M.D. Department of Orthopedic Surgery , Beth Israel Deaconess 
Medical Center, Brigham and Women’s Hospital, Massachusetts General Hospital , 
 Boston , MA , USA 
xiiiContributors
 Michael D. McKee , M.D., F.R.C.S(c) Division of Orthopedic Surgery, 
Department of Surgery , University of Toronto, St. Michael’s Hospital , Toronto , ON , 
 Canada 
 Samir Mehta , M.D. Orthopedic Trauma and Fracture Service, Department of 
Orthopedic Surgery , Hospital of the University of Pennsylvania , Philadelphia , 
 PA , USA 
 Hassan R. Mir , M.D. Department of OrthopedicSurgery and Rehabilitation , 
 Vanderbilt University Medical Center , Nashville , TN , USA 
 Surena Namdari , M.D., M.Sc Department of Orthopedic Surgery , University of 
Pennsylvania , Philadelphia , PA , USA 
 Kevin R. O’Neill , M.D., M.S. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center East , Nashville , TN , USA 
 Robert V. O’Toole , M.D. Department of Orthopedic Traumatology , R Adams 
Cowley Shock Trauma Center , Baltimore , MD , USA 
 William T. Obremskey , M.D., M.P.H. Department of Orthopedic Surgery and 
Rehabilitation , Vanderbilt University Medical Center , Nashville , TN , USA 
 Steven A. Olson , M.D. Department of Orthopedic Surgery , Orthopedic Trauma 
Duke University Medical Center, Duke University Hospital , Durham , NC , USA 
 Brendan M. Patterson , M.D. Department of Orthopedic Surgery , MetroHealth , 
 Cleveland , OH , USA 
 Edward A. Perez , M.D. Department of Orthopedic Surgery , University of 
Tennessee/Campbell Clinic , Memphis , TN , USA 
 Dave Polga , M.D. Department of Orthopedic Surgery , Marsh fi eld Clinic , 
 Marsh fi eld , WI , USA 
 William M. Ricci , M.D. Department of Orthopedic Surgery , Barnes-Jewish 
Hospital , St. Louis , MO , USA 
 David Ring , M.D., Ph.D. Department of Orthopedic Surgery , Harvard Medical 
School, Massachusetts General Hospital , Boston , MA , USA 
 Bill Ristevski , M.D., M.Sc. Division of Orthopedic Surgery, Department of 
Surgery, Hamilton General Hospital , Hamilton , ON , Canada 
 Edward K. Rodriguez , M.D., Ph.D. Department of Orthopedic Surgery , 
 Beth Israel-Deaconess Medical Center, Harvard Medical School , Boston , MA , USA 
 Matthew I. Rudloff , M.D. Department of Orthopedic Surgery , University of 
Tennessee/Campbell Clinic , Memphis , TN , USA 
 Scott P. Ryan , M.D. Department of Orthopedic Surgery , Tufts University Medical 
Center , Boston , MA , USA 
xiv Contributors
 Marlis T. Sabo , M.D., M.S.C., F.R.C.S.C. Department of Surgery , Victoria 
Hospital , London , ON , Canada 
 David W. Sanders , M.D., M.S.C., F.R.C.S.C. Department of Surgery , Victoria 
Hospital , London , ON , Canada 
 Roy W. Sanders , M.D. Department of Orthopedics , Florida Orthopedic Institute, 
Tampa General Hospital , Tampa , FL , USA 
 Andrew H. Schmidt , M.D. Department of Orthopedic Surgery , Hennepin County 
Medical Center, University of Minnesota , Minneapolis , MN , USA 
 Manish K. Sethi , M.D. Department of Orthopedic Surgery and Rehabilitation , 
 Vanderbilt University Medical Center , Nashville , TN , USA 
 Jodi Siegel , M.D. Department of Orthopedic Surgery , UMass Memorial Medical 
Center, University of Massachusetts Medical School , Worcester , MA , USA 
 Andrew K. Simpson , M.D., M.H.S. Harvard Combined Orthopedic Surgery , 
 Massachusetts General Hospital , Boston , MA , USA 
 Daniel J. Stinner , M.D. Department of Orthopedics and Rehabilitation , San 
Antonio Military Medical Center , Fort Sam Houston , TX , USA 
 Philipp N. Streubel , M.D. Department of Orthopedic Surgery and Rehabilitation , 
 Vanderbilt University Medical Center , Nashville , TN , USA 
 David C. Templemen , M.D. Department of Orthopedic Surgery , Hennepin County 
Medical Center , Minneapolis , MN , USA 
 Paul Tornetta III, M.D. Department of Orthopedic Surgery , Orthopedic Trauma, 
Boston Medical Center , Boston , MA , USA 
 Theo Tosounidis , M.D. Department of Surgery , Foothills Hospital, University of 
Calgary , Calgary , AB , Canada 
 Robert T. Trousdale , M.D. Department of Orthopedic Surgery , Mayo Medical 
Center, Mayo Medical School , Rochester , MN , USA 
 Jeffry Watson , M.D. Department of Orthopedic Surgery and Rehabilitation , 
 Vanderbilt University Medical Center , Nashville , TN , USA 
 John C. Weinlein , M.D. Department of Orthopedic Surgery , University of 
Tennessee/Campbell Clinic , Memphis , TN , USA 
 Part I 
 Evidence-Based Medicine 
in Orthopedic Trauma Surgery 
 Section editor—Mohit Bhandari 
3M.K. Sethi et al. (eds.), Orthopedic Traumatology: An Evidence-Based Approach, 
DOI 10.1007/978-1-4614-3511-2_1, © Springer Science+Business Media New York 2013
 Keywords Evidence-based medicine  Evidence-based orthopedics  Introduction 
 Hierarchy of evidence  Hierarchy of research studies  Parallel trial design 
 Factorial design 
 Introduction 
 The science of addressing orthopedic problems that confront orthopedic surgeons 
everyday requires a rigorous methodology to guide investigation and provide valid 
answers. The term “evidence-based medicine”, fi rst coined by Dr. Gordon Guyatt at 
McMaster University has become the standard for clinical investigation and critical 
appraisal. It has been de fi ned as the conscientious and judicious use of current best 
available evidence as the basis for surgical decisions [ 1– 3 ] . Application of the 
 evidence does not occur in isolation but rather with integration of surgical expertise 
and clinical circumstances, as well as with societal and patient values [ 4, 5 ] (Fig. 1.1 ). 
In addition, identifying and applying best available evidence requires a comprehen-
sive search of the literature, a critical appraisal of the validity and quality of avail-
able studies, astute consideration of the clinical situation and factors that may 
in fl uence applicability, and a balanced application of valid results to the clinical 
problem [ 6 ] . 
 C. Foote , M.D. (*)
 McMaster University , 2-18 Hill Street , Hamilton , ON , Canada L8P 1W7 
e-mail: clary.foote@medportal.ca 
 M. Bhandari , M.D., Ph.D., F.R.C.S.C. 
 Division of Orthopedic Surgery , McMaster University , Hamilton , ON , Canada 
 Chapter 1 
 Introduction to Evidence-Based Medicine 
 Clary Foote and Mohit Bhandari 
4 C. Foote and M. Bhandari
 I n 2000, Marc Swiontkowski introduced the evidence-based orthopedics (EBO) 
section of the Journal of Bone Surgery (JBJS) with a focus on higher levels of evi-
dence such as randomized control trials (RCTs) which recognized the de fi ciency of 
controlled studies in the orthopedic literature [ 7 ] . In 2003, the JBJS adopted EBM 
and the hierarchy of evidence for grading all clinical papers. Also during that year, 
Dr. Bhandari initiated the evidence-based orthopedic trauma section in the Journal 
of Orthopedic Trauma (JOT) [ 8 ] . Since then, the EBO initiative has grown into a 
global initiative and has become the common language at international orthopedic 
meetings. The American Orthopedic Society has recognized and incorporated EBO 
for utilization into clinical guidelines [ 9 ] . 
 Paramount to the understanding of “best available evidence” are the concepts of 
hierarchy of evidence, meta-analyses, study design, and precision of results. 
A familiarity with these concepts will aid the orthopedic surgeon in identifying, 
understanding, and incorporating best evidence into their practice. We begin here 
with an overview of the hierarchy of surgical evidence with attention paid to study 
designand methodological quality. Some of the common instruments to measure 
study quality are described, and we direct our readership to adjunctive educational 
resources. Finally, we conclude by clarifying misconceptions of EBO to reinforce 
its underpinning principles that help the reader interpret the surgical evidence 
 presented in this text. 
 Hierarchy of Research Studies 
 To understand the concept of best evidence a surgeon must fi rst be knowledgeable 
about the hierarchy of surgical evidence. The hierarchy can be thought of as a 
classi fi cation system to provide a common language for communication and a basis 
 Fig. 1.1 The triumvirate of 
evidence-based orthopedics 
(EBO) to improve best 
practice in orthopedics. 
Reproduced with permission 
from Tilburt JC, et al. J Eval 
Clin Pract. 2008;14:721–5 
 
51 Introduction to Evidence-Based Medicine
for review of available evidence. Research studies range from very high quality to 
low quality which are largely based on the study design and methodological quality 
 [ 10 ] . In general, high-quality studies minimize bias and thus increase our con fi dence 
in the validity of results. Bias can be de fi ned as systematic error in a research study 
that impacts outcome such that it differs from the truth [ 11 ] . There are several avail-
able systems to formulate the level of evidence of a given study. The Oxford Centre 
for Evidence-Based Medicine has published hierarchies for therapeutic, prognostic, 
harm, prevalence, and economic analyses [ 12 ] . For each of aforementioned subcat-
egories, there is a hierarchy of evidence with unique clinical signi fi cance [ 13, 14 ] . 
JBJS has incorporated the Oxford System in order to develop a hierarchy for 
 orthopedic studies (Table 1.1 ). For the purposes of this text, when we refer to the 
“hierarchy” or “level of evidence,” we will be referring to this table. 
 In orthopedic traumatology, therapeutic studies are of central importance. For 
instance, they may tell us the healing and complication rates of reamed versus 
unreamed technique for intramedullary nailing of tibial shaft fractures [ 15 ] . When 
evaluating a study of a surgical or therapeutic intervention one must identify the 
study design as an initial step to identify best evidence [ 16 ] . The highest level of 
evidence lies in RCTs and systematic reviews or meta-analyses of high-quality 
RCTs [ 17, 18 ] . These are referred to as level I trials [ 2 ] . The process of randomiza-
tion is the best research tool to minimize bias by distributing known and unknown 
prognostic variables uniformly between treatment groups [ 19, 20 ] . Available evi-
dence suggests that non-randomized studies tend to overestimate [ 21 ] or underesti-
mate [ 22 ] treatment effects. Reviews of RCTs use rigorous methodology to improve 
sample size and precision of study results and are therefore considered the highest 
level of evidence when reviewed studies are of suf fi cient methodological quality 
(Table 1.1 ) [ 23 ] . Reviews may statistically combine results (meta-analyses) when 
trial reporting allows or provide a qualitative overview of the results of included 
studies (systematic reviews) [ 24 ] . Unrandomized prospective studies such as cohort 
studies (also known as prospective comparative studies) provide weaker empirical 
evidence, as they are prone to several biases [ 22 ] . For instance, treatment allocation 
is uncontrolled and therefore treatment cohorts may differ in prognosis from the 
outset due to selection bias (Table 1.2 ) [ 25 ] . Retrospective case–control studies 
assess past characteristics and exposures in cases as compared with controls. These 
studies are subject to several types of bias including selection and recall bias 
(Table 1.2 ). Matching treatment and control groups for known prognostic variables 
(e.g., age, gender, functional level) may partially control for confounding variables 
but rarely suf fi ciently negates them. One can also “overmatch” groups such that the 
groups are so closely matched that the exposure rates between cohorts are analo-
gous [ 26 ] . In addition, the retrospective structure can lead to imprecise data collec-
tion and differential patient follow-up [ 27 ] . At the bottom of the evidence hierarchy 
are case reports, series, and expert opinion. Case series are uncontrolled, unsystem-
atic studies with a role mainly in hypothesis generation for future investigation and 
provide very little utility in guiding care. These reports are usually single-surgeon 
and single-center experiences which further impairs generalizability. 
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71 Introduction to Evidence-Based Medicine
 Study Quality and the Hierarchy of Evidence 
 When placing a study into the surgical hierarchy one must also consider study qual-
ity. In general, studies drop one level if they contain methodological problems 
(Table 1.1 ) [ 12, 28 ] . RCTs are only considered level I evidence when they have 
proper institution of safe-guards against bias (Table 1.3 ), high precision (narrow 
con fi dence intervals), and high levels of patient follow-up; lesser quality RCTs are 
assigned to level II evidence. Several instruments have been validated to assess the 
quality of RCTs which include the Jadad (range 0–5), Delphi list (range 0–9), and 
numeric rating scale (NRS; range 1–10). For example, the Jadad Scale is the sim-
plest and most widely utilized instrument to assess methodological quality of clini-
cal trials (Table 1.4 ) [ 29 ] . In the orthopedic literature it has been used to evaluate the 
quality of research in a particular fi eld [ 30– 32 ] , set a minimum standard for included 
papers in a systematic review or meta-analysis [ 33 ] , or for critical appraisal of an 
individual paper. The Jadad Scale contains three main areas of assessment: random-
ization, blinding, and loss to follow-up (Table 1.4 ). In addition, quality scoring sys-
tems exist for observational studies (i.e., cohort and case–control) such as the 
Newcastle–Ottawa Scale for Cohort Studies [ 34 ] . For cohort studies, this tool 
assesses the rigor of cohort selection and comparability, ascertainment of exposure, 
outcome assessment (e.g., blinded assessment), and follow-up. From this, we have 
summarized crucial methodological elements of quality studies in Table 1.3 . 
Although the actual validated instruments need not be used rigorously in everyday 
orthopedics, these quality criteria should be of central concern to the orthopedic 
surgeon in assessing the validity of results of published studies. 
 Table 1.2 De fi nitions of bias types in therapeutic studies 
 Types of biases De fi nition 
 Selection bias Treatment groups differ in measured and unmeasured characteristics and 
therefore have differential prognosis due to systematic error in creating 
intervention groups [ 35 ]. 
 Recall bias Patients who experience an adverse outcome are more likely to recall 
exposure than patients who do not sustain an adverse outcome [ 27, 70 ]. 
 Detection bias Biased assessment of outcome. May be in fl uenced by such things as prior 
knowledge of treatment allocation or lack of independent af fi liation 
within a trial [ 25 ]. 
 Performance bias Systematic differences in the care provided to cohorts are independent of 
the intervention being evaluated [ 25, 71 ]. 
 Attrition bias Occurs when those that drop out of a study are systematically different 
from those that remain.Thus, fi nal cohorts may not be representative 
of original group assignments [ 2, 67 ]. 
 Expertise bias Occurs when a surgeon involved in a trial has differential expertise (and/or 
convictions) with regard to procedures in a trial where trial outcomes 
may be impacted by surgeon competency and/or beliefs rather than 
interventional ef fi cacy [ 72 ]. 
8 C. Foote and M. Bhandari
 Table 1.3 Some essential methodological components of high-quality studies 
 Item Study design Description 
 A priori de fi ned 
study protocol 
 RCT and 
observational 
 A protocol is critical to establish a priori primary 
and secondary outcomes which will require 
speci fi c considerations, resources, and sample 
size. A priori outcomes maximize the bene fi ts of 
cohort assignment (e.g., randomization) and 
limit overanalyzing trial data that leads to a 
higher rate of identifying signi fi cant differences 
by chance alone. 
 Prospective RCT and 
observational 
 Studies started before the fi rst patient enrolled to 
improve cohort assignments, blinding, precision 
of data collection, completeness of follow-up, 
and study directness. 
 Power analysis RCT or 
observational 
 Determination of the appropriate sample size to 
detect a pre-speci fi ed difference of clinical 
signi fi cance between cohorts. Based on standard 
deviation measurements from previous 
reputable studies. Ensures that a study has 
suf fi cient power to detect a clinically signi fi cant 
difference. 
 Exclusion and 
inclusion criteria 
 RCT and 
observational 
 De fi ning the study population of interest and 
limiting patient factors which may confound 
outcomes greatly improves the generalizability 
of study results. 
 Clinically relevant 
and validated 
outcome measures 
 RCT and 
observational 
 The ef fi cacy of an intervention should be based on 
outcomes that are important to patients using 
instruments validated in capturing this clinical 
information. 
 Blinding RCT and 
observational 
 Surgeon blinding may not be possible, but blinding 
patients, outcome assessors, data analysts, 
authors of the results section, and outcomes’ 
adjudicators are imperative to protect against 
detection and performance biases. 
 Randomization RCT Safe-guard against selection bias by ensuring equal 
distribution of prognostic characteristics 
between cohorts. 
 Concealment RCT Investigators must be blinded to treatment 
allocation of patients to protect against 
undue in fl uence on treatment allocation 
(i.e., selection bias). 
 Complete follow-up RCT and 
observational 
 Complete follow-up of all patients should always 
be sought [ 67 ] . Appreciable risk of attrition bias 
exists when follow-up is less than 80% [ 68 ]. 
 Expert-based design RCT A surgeon with expertise in one of the procedures 
being evaluated in a trial is paired with a 
surgeon with expertise in the other procedure. 
Subjects are then randomized to a surgeon, who 
performs only one of the interventions (i.e., the 
procedure that he/she has expertise and/or a 
belief that it is the superior procedure) [ 69 ] 
A safe-guard for expertise bias. 
91 Introduction to Evidence-Based Medicine
 Recently, the Consolidated Standards of Reporting Trials (CONSORT) Group 
published updated guidelines on how to report RCTs [ 35 ] . Previous systematic 
review of the surgical literature has reported poor compliance of surgical RCTs with 
its recommendations and endorsed educational initiatives to improve RCT report-
ing [ 36 ] . Although a thorough review of this document is beyond the scope of this 
chapter, it suf fi ces to say that it serves as an excellent overview to aid in planning, 
executing, and reporting RCTs. 
 Randomized Surgical Trials: An Overview 
of Speci fi c Methodologies 
 RCTs are considered the optimal study design to assess the ef fi cacy of surgical inter-
ventions [ 28 ] . RCTs in the orthopedic literature have been described as explanatory 
(also called mechanistic) or pragmatic [ 37 ] . The explanatory trial is a rigorous study 
design that involves patients who are most likely to bene fi t from the intervention and 
asks the question of whether the intervention works in this patient population who 
receive treatment. Pragmatic trials include a more heterogeneous population, usually 
involve a less rigorous protocol and question whether the intervention works to whom 
it was offered [ 38 ] . The explanatory trial measures the ef fi cacy of the intervention 
under ideal conditions, whereas the pragmatic trial measures the effectiveness of the 
intervention in circumstances resembling daily surgical practice. For that reason prag-
matic trials have been said to be more generalizable but this comes at the cost of 
reduced study power due to patient heterogeneity which results in a larger range of 
treatment effects (increased noise). Explanatory and pragmatic approaches should be 
thought of as a continuum, and any particular trial may have aspects of each. The opti-
mal trial design depends on the research question, the complexity of the intervention, 
and the anticipated bene fi t of the new intervention to the patient. Randomized trials are 
best suited to assess interventions with small-to-medium treatment effects. The smaller 
the anticipated effect, the more an investigator should consider optimizing the partici-
pant pool and intervention to provide clean results (explanatory trial) [ 38, 39 ] . 
 Orthopedic surgery trials pose many methodological challenges to researchers. 
These include dif fi culties with recruitment of an adequate number of patients, blinding, 
 Table 1.4 Jadad Scale for assessment of methodological quality of a clinical trial [ 29 ] 
 Primary questions: 
 1. Was the study described as randomized? 
 2. Was the study described as double blind? 
 3. Was there a description of withdrawals and dropouts? 
 Two addition points can be given if the following criteria are met : 
 4. The method of randomization was described in the paper, and that method was appropriate 
 5. The method of blinding was described, and it was appropriate 
 One point is deducted for each of the following criteria: 
  The method of randomization was described, but was inappropriate 
  The method of blinding was described, but was inappropriate 
 Jadad Score 0 (poor quality) to 5 (high quality) 
10 C. Foote and M. Bhandari
differential cointervention, and outcome assessment. These dif fi culties are re fl ected in 
the quality of the current orthopedic literature. A previous review of orthopedic RCTs 
showed that a high percentage failed to report concealment of allocation, blinding, and 
reasons for excluding patients [ 40– 42 ] . The results of these RCTs may be misleading 
to readers and there is a growing consensus that larger trials are required [ 43 ] . A recent 
RCT has shown that many of these problems can be circumvented with multicenter 
surgical RCTs that include strict guidelines for cointervention and contain a blinded 
adjudication committee to determine outcomes [ 44 ] . 
 The orthopedic community generally agrees that RCTs are the future of orthope-
dic research, but there have been many arguments against them. These include ethi-
cal assertions about patient harm which include: (1) surgeons performing different 
operations at random where they may be forced to perform a procedure at which 
they are less skilled and comfortable performing; (2) conducting RCTs which involve 
withholding care such as in a placebo-controlled trial; and (3) inability to blind sur-
geons and the dif fi culty in blinding patients unless a sham RCT is conducted [ 25 ] . 
Although sham RCTs that facilitate patient blinding have been published, many eth-
ics committees continueto deny its use on the basis of potential harm to patients who 
receive sham treatment [ 45, 46 ] . To help answer the question of harm in sham RCTs, 
several authors are currently conducting a systematic review looking at outcomes in 
sham trials (unpublished study). On another note, new innovative designs have 
emerged to address some of the ethical problems with surgical RCTs. 
 The Expertise-Based Design 
 In surgical trials the ethical dilemma can present if the surgeon believes one inter-
vention is superior or has more expertise with one procedure, but is forced to per-
form the other procedure due to random patient allocation. In such a circumstance, 
it is unethical for the surgeon to be involved in the trial. To address this problem, 
Dr. Devereaux has published extensively on the expertise-based design where the 
patient is randomized to one of the two groups of surgeons and not to the procedure 
itself. This is in contrast to the parallel RCT where surgeons perform both proce-
dures in random order. This avoids the aforementioned ethical dilemma and also 
minimizes performance bias where the results of the trial may be heavily impacted 
by surgeon experience or comfort. The downside of expertise-based design is that in 
some research areas, such as trauma surgery, both surgeon groups need to be avail-
able at all times to perform their designated intervention. This may limit feasibility 
in small centers with scarce resources. 
 Parallel Trial Design 
 The most commonly utilized and simplest design is the parallel randomized trial. 
Participants are assigned to one of two or more treatment groups in a random order. 
The most basic of these involves two treatments groups – a treatment and control arm. 
111 Introduction to Evidence-Based Medicine
Trials can have more than two arms to facilitate multiple comparisons, but this 
requires larger sample sizes and increases the complexity of analysis. 
 Factorial Design 
 The factorial trial enables two or more interventions to be evaluated both individually 
and in combination with one another. This trial design is thought to be economical in 
some settings because more than one hypothesis (and treatment) can be tested within 
a single study. For example, Petrisor et al. [ 47, 48 ] conducted a multicenter, blinded 
randomized 2 × 3 factorial trial looking at the effect of irrigation solution (castile soap 
or normal saline) and pressure (high versus low versus very low pressure lavage) on 
outcomes in open fracture wounds. The corresponding 2 × 3 table is shown in Table 1.5 . 
From this table the investigator wound compare the 1,140 patients receiving soap with 
the 1,140 who received saline solution. Concurrently, comparison can be made 
between each of the pressure categories with 760 participants. 
 With factorial designs there may be interaction between the interventions. That 
is, when treatments share a similar mechanism of action, the effect of one treatment 
may be in fl uenced by the presence of the other. If the treatments are commonly 
coadministered in surgical practice (such as the aforementioned lavage study), then 
this trial design is ideal, as it allows for assessment of the interaction to identify the 
optimal treatment combination. Treatment interactions may be negative (antagonistic) 
or positive (synergistic), which reduce or increase the study power, respectively. 
This consequently affects sample size, and therefore potential interactions should be 
considered in the design phase of the study. 
 Other Randomized Designs 
 In surgical trials the unit of randomization is often the patient or the limb of interest 
 [ 15, 47 ] . In other words, when we randomize to one treatment versus another, we 
are usually talking about randomizing patients. In some circumstances, however, 
randomizing patients may not be feasible or warranted. When the intervention is at 
an institutional or department level, such as with implementation of a new 
 Table 1.5 A 2 × 3 factorial trial table from the fl uid lavage in open fracture wounds (FLOW) 
randomized trial 
 Gravity fl ow pressure Low pressure High pressure Total 
 Soap solution 380 380 380 1,140 
 Saline 380 380 380 1,140 
 Total 760 760 760 2,280 
 This study had a target sample size of 2,280 participants and was designed to assess the impact of 
irrigation solution (soap or saline = 2 categories) and lavage pressure (gravity fl ow, low, and high 
pressure = 3 categories) in open fracture wounds [ 73 ] 
12 C. Foote and M. Bhandari
process, guideline, or screening program, patient randomization is dif fi cult and 
often impossible. This is for several reasons: (1) surgeons or health care practitio-
ners are unlikely to use a new guideline for one patient and not the other; (2) patients 
randomized to different interventions will often educate each other (a process called 
contamination); and (3) department wide programs are often expensive and 
challenging to implement, so running multiple programs is not practical or eco-
nomical. In these circumstances, it is best to randomize institutions, departments, or 
geographical areas. This process is called cluster randomization. For instance, if one 
were to implement a chewing tobacco cessation program among major league base-
ball players, it would make more sense to randomize teams to the cessation program 
rather than individual players. Two important aspects of cluster trials are: (1) par-
ticipants within clusters are more similar with regard to prognostic factors than 
between clusters and (2) a suf fi cient number of clusters must be available to provide 
prognostic balance and suf fi cient power. In general, because patients within clusters 
are similar, there is a reduction power and an increased required sample size of 
cluster trials. In the analysis, one can compare the outcomes of entire clusters or 
individuals. Individual patient analysis requires an estimate of patient similarity 
(called an intraclass correlation coef fi cient). The more similar the participants are 
within clusters, the higher the intraclass correlation coef fi cient, and the required 
sample size is consequently greater to reach signi fi cance. 
 In crossover trials patients are randomized to a treatment and then receive the 
other treatment after a designated period of time. Each participant serves as their 
own control when a within patient analysis is conducted. These studies have 
signi fi cant power but are rarely conducted in orthopedic surgery because they 
require chronic diseases with treatments that are quickly reversible once stopped. 
For example, Pagani et al. [ 49 ] conducted a crossover trial assessing the gait correc-
tion of 4-valgus and neutral knee bracing in patients with knee OA. All patients 
performed gait and stair climbing assessments without an orthosis and then were 
randomized to one of the two bracing arms for 2 weeks followed by crossover to the 
other bracing arm for 2 weeks. Because of the power of this analysis, they demon-
strated a statistically signi fi cant improvement in gait mechanics with 4-valgus 
 bracing with only 11 patients. 
 Special Considerations Within the Hierarchy 
 In addition to reviews of level II studies [ 50 ] , reviews of high-quality RCTs with 
inconsistent results [ 51 ] are also regarded as level II evidence (Table 1.1 ). For 
instance, Hopley et al. performed a meta-analysis comparing total hip arthroplasty 
(THA) to hemiarthroplasty (unipolar and bipolar) which included seven RCTs, three 
quasi-randomized, and eight retrospective cohort studies. This review reported 
reduced reoperation rates and better functional improvements after THA than hemi-
arthroplasty. However, from review of this study’s forest plot of randomized studies, 
131 Introduction to Evidence-BasedMedicine
one can see that there is a wide range in point estimates leading to imprecision 
within their pooled effect size (Fig. 1.2 ). This analysis encountered methodological 
issues such as lack of concealment, heterogeneity of study inclusion criteria, and 
type of hemiarthroplasty; all of these factors would negatively affect this meta- 
analysis’s rating within the hierarchy. In addition, the included review of retrospec-
tive cohort studies would be regarded as level III evidence (Fig. 1.2 ; Table 1.1 ). 
 Fig. 1.2 Sample forest plot that shows the point estimates and 95% con fi dence intervals of individual 
primary studies and pooled effect sizes represented as a relative risk ( diamond ). This meta-analysis 
provided separate pooled effect sizes for each type of study design and an overall pooled estimate 
shown at the bottom . Estimates to the left favor total hip arthroplasty and to the right hemiarthro-
plasty. Reproduced with permission from Hopley C, Stengel D, Ekkernkamp A, et al. Primary total 
hip arthroplasty versus hemiarthroplasty for displaced intracapsular hip fractures in older patients: 
systematic review. BMJ. 2010;340:c2332 
 
14 C. Foote and M. Bhandari
 Grades of Recommendation: From the Bench 
to the Operating Room 
 The quality of best available evidence and the magnitude of treatment effect reported 
play a central role in the strength of clinical practice recommendations. A recom-
mendation for or against an intervention is based on a comprehensive systematic 
review of available evidence, evaluation of the methodological quality of available 
studies, and focus group discussion of subspecialty experts to achieve consensus. In 
2004, the Grading of Recommendation Assessment, Development, and Evaluation 
(GRADE) Working Group developed a system for scoring the quality of evidence 
(Table 1.6 ) [ 52 ] . This scoring system places more weight on studies with better 
design, higher methodological quality, and larger treatment effects, but also consid-
ers factors such as directness [ 53 ] . The GRADE Criteria are applied to all critical 
outcomes. Once the evidence is “graded” and several factors such as calculation of 
baseline risk in the target population, feasibility of the proposed intervention, and a 
bene fi t versus harm assessment are completed, a recommendation level is assigned 
which includes one of the following (1) do it; (2) probably do it; (3) toss up; (4) 
probably do not do it; and (5) do not do it [ 38, 39 ] . These recommendations guide 
surgeons by suggesting that most (items 1 and 4) or many (items 2 and 4) well-
informed surgeons would make a particular decision, based on systematic review of 
the literature. The GRADE approach provides a basic foundation for translating 
evidence into practice and serves as a useful communication tool for clinicians and 
 Table 1.6 Modi fi ed GRADE quality assessment criteria [ 53 ] 
 Quality of evidence Study design Lower if a Higher if a 
 High Randomized trial Study quality : 
 −1 Serious limitations 
 −2 Very serious 
limitations 
 −1 Important 
 inconsistency 
 Directness : 
 −1 Some uncertainty 
 −2 Major uncertainty 
 −1 Sparse data 
 −1 High probability 
of Reporting bias 
 Strong association : 
 +1 Strong, no plausible 
confounders, consistent 
and direct evidence b 
 +2 Very strong, no major 
threats to validity and 
direct evidence c 
 +1 Evidence of a dose–
response gradient 
 +1 All plausible confound-
ers would have reduced 
the effect 
 Moderate Quasirandomized 
trial 
 Low Observational study 
 Very low Any other evidence 
 
a
 1 = move up or down one grade (e.g., from high to moderate). 2 = move up or down two grades 
(e.g., from high to low). The highest possible score is high (4) and the lowest possible score is very 
low (1). Thus, for example, randomized trials with a strong association would not move up a grade 
 
b
 A relative risk of >2 (<0.5), based on consistent evidence from two or more observational studies, 
with no plausible confounders 
 
c
 Available studies provide direct comparisons between alternative treatments in similar participant 
populations 
151 Introduction to Evidence-Based Medicine
review panels. However, even valued input and consensus from expert panels does 
not replace a sound understanding of the available evidence (e.g. from a critical 
appraisal of a meta-analyses) and good clinical judgment. Hence, we return to the 
essence of EBO which considers best available evidence, clinical judgment, patient 
values, and clinical circumstances when making treatment decisions (Fig. 1.1 ). 
 Evidence-Based Orthopedics: Advances and Misconceptions 
 EBM has been recognized as one of the top 15 medical discoveries of the last 
160 years. In the past decade it revolutionized clinical research and care by provid-
ing the basis for the development of clinical trials, systematic review, and validated 
outcomes. International standards have been developed such as the Oxford Centre 
for Evidence-Based Medicine, the Cochrane Collaboration, and Britain’s Center for 
Review, which are providing updated systematic reviews of the effects of medical 
and surgical care [ 54 ] . In orthopedics, JBJS has fully incorporated the hierarchy of 
evidence into all published manuscripts, and this has been utilized in Annual 
Meetings of the American Academy of Orthopedic Surgeons (AAOS) [ 55 ] . As a 
consequence, the overall quality of clinical trials and systematic reviews in orthope-
dics appears to be improving [ 23, 56 ] . 
 Improving the validity of orthopedic studies is only one facet of EBO in its pur-
suit to improving standards in orthopedic practice. EBO also requires a willingness 
of an orthopedic society, for example, the AAOS in this case, to incorporate best 
evidence into practice [ 57 ] . Traditionally, there has been a resistance to perform 
well-designed studies in orthopedics and misconceptions about the practice of EBO 
 [ 58, 59 ] . In contrast, a recent international cross-sectional survey among International 
Hip Fracture Research Collaborative (IHFRC) Surgeons revealed that most sur-
geons are willing to change their practice based on large-scale clinical trial results 
 [ 60 ] . Thus, it appears that orthopedists are recognizing the need for higher standards 
to ensure best care for patients with musculoskeletal conditions. 
 Despite the global movement of EBO, misconceptions about it exist. There have 
been criticisms that EBO only gives information about the average patient and that 
simple application of trial results is analogous to “cook-book” medicine [ 16, 61 ] . 
The approach of EBO is actually exactly the opposite. EBO utilizes a bottom-up 
approach which begins with a surgical problem and incorporates best available evi-
dence, surgical expertise and experience, the clinical context, and patient prefer-
ences. Surgical expertise and a working understanding of EBO are essential to 
appreciate if the available evidence applies well to the individual patient and clinical 
circumstances, and if so, how it should be applied. For example, if one were to 
encounter the 65-year-old marathon runner with a displaced femoral neck fracture 
after a fall, one must consider the available evidence of improved outcomes of THA 
as compared to hemiarthroplasty and internal fi xation, the current limitations of this 
literature, the patient’s functional status and physiologic age, and patient prefer-
ences and expectations with regard to the complication pro fi le and functional out-
comes of these procedures [ 51, 62, 63 ] . 
16 C. Foote and M. Bhandari
 Some have equated EBO with RCTs and meta-analysis. On the contrary, EBO 
proposes to use the most appropriate studydesign and methodology to answer the 
surgical question with maximal validity. RCTs are more effective when the condi-
tion is common rather than when it is rare. For instance, many conditions in ortho-
pedic oncology are too scarce to permit an RCT but EBO advocates that studies in 
this fi eld institute as many safe-guards as possible to limit bias, to focus on out-
comes that are important to patients, and to perform systematic review when pos-
sible [ 64 ] . In addition, evaluation of diagnostic ef fi cacy is best answered by 
cross-sectional studies rather than RCTs. Questions regarding biomechanics and 
prosthetic wear-properties are often best addressed by studies in basic science. 
Despite this, randomized trials have claimed much of the focus of EBO because of 
their important role in providing valid outcomes for surgical interventions 
(Table 1.1 ). Thus, it is important to keep in mind that many factors determine the 
ideal study design that best answers the clinical problem. Such considerations 
include the type of question being asked (e.g., therapeutic ef fi cacy, diagnosis), fre-
quency of the condition, ethics of intervention, the quality and uncertainties of 
available evidence, and surgical equipoise. 
 Closing Comments 
 Ultimately, becoming an evidence-based orthopedic surgeon is not a simple task. 
One must understand the hierarchy of evidence, from meta-analysis of RCTs to 
clinical experience. In making surgical decisions a surgeon should know the strength 
of best available evidence and the corresponding degree of uncertainty. The process 
of exploration of evidence to answer speci fi c questions is equally critical. The abil-
ity to search the available literature, evaluate the methodological quality of studies 
to identify best evidence, determine the applicability of this information to the 
patient, and appropriately store this information for further reference requires edu-
cation and practice. For educational modules on these topics we direct you toward 
several additional resources to this text including Clinical Research for Surgeons 
 [ 25 ] , the Users’ Guide of the Medical Literature [ 2 ] , the JBJS Users’ Guides to the 
Surgical Literature [ 65 ] , and the Journal of Orthopedic Trauma Evidence-based 
Orthopedic Trauma Summaries [ 8 ] . 
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 Part II 
 Spine Trauma 
 Section editor—Mitchel B. Harris 
23M.K. Sethi et al. (eds.), Orthopedic Traumatology: An Evidence-Based Approach, 
DOI 10.1007/978-1-4614-3511-2_2, © Springer Science+Business Media New York 2013
 Keywords Cervical spine clearance • Cervical spine trauma initial management • 
 Clinical assessment of cervical spine injury • The Advanced Trauma Life Support 
(ATLS) protocol • Asymptomatic • Temporarily non-assessable • Symptomatic • 
 Obtunded 
 GB: 25-Year-Old Male with Neck Pain 
 Case Presentation 
 GB is a 25-year-old male who presents after an all terrain vehicle (ATV) accident. 
At the scene the patient demonstrates a GCS score of 12 complaining of chest pain 
and is placed in a cervical collar. The patient presents to the local emergency room 
via EMS. On primary survey the patient demonstrates a