AAO Update on General Medicine 2022-2023 PDF

1 Update on General Medicine 2022–2023 BCSC Basic and Clinical ® Science Course™ Editorial Committee Herbert J. Ingraham, MD, Chair Darin K. Bowers, MD A. Luisa Di Lorenzo, MD Peggy H. Gramates, MD Ariane D. Kaplan, MD Paul J. Lama, MD Steven L. Mansberger, MD, MPH 1 Update on General Medicine Last major revision 2019–2020 2022–2023 BCSC Basic and Clinical Science Course™ Published after collaborative review with the European Board of Ophthalmology subcommittee The American Academy of Ophthalmology is accredited by the Accreditation Council for Con- tinuing Medical Education (ACCME) to provide continuing medical education for physicians. The American Academy of Ophthalmology designates this enduring material for a maximum of ™ 10 AMA PRA Category 1 Credits. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Originally released June 2019; reviewed for currency August 2021; CME expiration date: June 1, 2023. ™ AMA PRA Category 1 Credits may be claimed only once between June 1, 2019, and the expiration date. ® BCSC volumes are designed to increase the physician’s ophthalmic knowledge through study and review. Users of this activity are encouraged to read the text and then answer the study questions provided at the back of the book. ™ To claim AMA PRA Category 1 Credits upon completion of this activity, learners must demon- strate appropriate knowledge and participation in the activity by taking the posttest for Section 1 and achieving a score of 80% or higher. For further details, please see the instructions for requesting CME credit at the back of the book. The Academy provides this material for educational purposes only. It is not intended to represent the only or best method or procedure in every case, nor to replace a physician’s own judgment or give specific advice for case management. Including all indications, contraindications, side effects, and alternative agents for each drug or treatment is beyond the scope of this material. All information and recommendations should be verified, prior to use, with current information included in the manufac- turers’ package inserts or other independent sources, and considered in light of the patient’s condition and history. Reference to certain drugs, instruments, and other products in this course is made for illustrative purposes only and is not intended to constitute an endorsement of such. Some material may include information on applications that are not considered community standard, that reflect indications not included in approved FDA labeling, or that are approved for use only in restricted research settings. The FDA has stated that it is the responsibility of the physician to determine the FDA status of each drug or device he or she wishes to use, and to use them with appropriate, informed patient consent in compliance with applicable law. The Academy specifically disclaims any and all liability for injury or other damages of any kind, from negligence or otherwise, for any and all claims that may arise from the use of any recommendations or other information contained herein. All trademarks, trade names, logos, brand names, and service marks of the American Academy of Oph- thalmology (AAO), whether registered or unregistered, are the property of AAO and are protected by US and international trademark laws. These trademarks include, but are not limited to, AAO; AAOE; AMERICAN ACADEMY OF OPHTHALMOLOGY; BASIC AND CLINICAL SCIENCE COURSE; BCSC; EYENET; EYEWIKI; FOCAL POINTS; FOCUS DESIGN (logo on cover); IRIS; IRIS REGIS- TRY; ISRS; OKAP; ONE NETWORK; OPHTHALMOLOGY; OPHTHALMOLOGY GLAUCOMA; OPHTHALMOLOGY RETINA; OPHTHALMOLOGY SCIENCE; OPHTHALMOLOGY WORLD NEWS; PREFERRED PRACTICE PATTERN; PROTECTING SIGHT. EMPOWERING LIVES.; THE OPHTHALMIC NEWS AND EDUCATION NETWORK. Cover image: From BCSC Section 12, Retina and Vitreous. Confocal scanning laser ophthalmoscopy multicolor fundus image (30° field of view) of a healthy eye. (Courtesy of Lucia Sobrin, MD.) Copyright © 2022 American Academy of Ophthalmology. All rights reserved. No part of this publication may be reproduced without written permission. Printed in China. Basic and Clinical Science Course Christopher J. Rapuano, MD, Philadelphia, Pennsylvania Senior Secretary for Clinical Education J. Timothy Stout, MD, PhD, MBA, Houston, Texas Secretary for Lifelong Learning and Assessment Colin A. McCannel, MD, Los Angeles, California BCSC Course Chair Section 1 Faculty for the Major Revision Herbert J. Ingraham, MD Ariane D. Kaplan, MD Chair Ann Arbor, Michigan Danville, Pennsylvania Darin K. Bowers, MD Paul J. Lama, MD Lynchburg, Virginia Rochelle Park, New Jersey A. Luisa Di Lorenzo, MD Steven L. Mansberger, MD, MPH Troy, Michigan Portland, Oregon Peggy H. Gramates, MD Pineville, Louisiana The Academy wishes to acknowledge the following committees for review of this edition: Committee on Aging: Andrew G. Lee, MD, Houston, Texas Vision Rehabilitation Committee: Joseph L. Fontenot, MD, Mobile, Alabama Practicing Ophthalmologists Advisory Committee for Education: Steven J. Grosser, MD, Pri- mary Reviewer, Golden Valley, Minnesota; Bradley D. Fouraker, MD, Chair, Tampa, Florida; Alice Bashinsky, MD, Asheville, North Carolina; David J. Browning, MD, PhD, Charlotte, North Carolina; Cynthia S. Chiu, MD, Oakland, California; Stephen R. Klapper, MD, Carmel, Indiana; Troy M. Tanji, MD, Waipahu, Hawaii; Michelle S. Ying, MD, MSPH, Ladson, South Carolina The Academy also wishes to acknowledge the following committee for assistance in devel- oping Study Questions and Answers for this BCSC Section: Self-Assessment Committee: Deepa Abraham, MD, Seattle, Washington; William R. Barlow, MD, Salt Lake City, Utah; William L. Becker, MD, St Louis, Missouri; Michele M. Bloomer, MD, San Francisco, California; John J. Chen, MD, PhD, Rochester, Minnesota; Zelia M. Correa, MD, Baltimore, Maryland; Deborah M. Costakos, MD, Milwaukee, Wisconsin; Theodore Curtis, MD, Mount Kisco, New York; Laura C. Fine, MD, Boston, Massachusetts; Robert E. Fintelmann, MD, Phoenix, Arizona; Mark Greiner, MD, Iowa City, Iowa; Jeffrey M. Goshe, MD, Cleveland, Ohio; Paul B. Griggs, MD, Seattle, Washington; David R. Hardten, MD, Minnetonka, Minnesota; Rachel M. Huckfeldt, MD, Boston, Massachusetts; Sarah S. Khodadadeh, MD, Vero Beach, Florida; Douglas R. Lazzaro, MD, Brooklyn, New York; Amanda C. Maltry, MD, Minneapolis, Minnesota; Brian Privett, MD, Cedar Rapids, Iowa; Sunita Radhakrishnan, MD, San Mateo, California; Jordan J. Rixen, MD, Lincoln, Nebraska; Mark I. Salevitz, MD, Scottsdale, Arizona; Ravi S. J. Singh, MD, Shawnee Mission, Kansas; Mitchell B. Strominger, MD, Reno, Nevada; Janet Y. Tsui, MD, Santa Clara, Cali- fornia; Ari L. Weitzner, MD, New York, New York; Zoë R. Williams, MD, Rochester, NY; Kimberly M. Winges, MD, Portland, Oregon In addition, the Academy wishes to recognize the important contributions of Jerry A. Dancik, MD, in the development of Chapter 3, and Lisa Henderson, MD, Linda Gadioli, and Brett Wheat in the development of Chapter 16. Finally, the Academy acknowledges the following consultants for their important work on Chapter 17: Angela R. Elam, MD, Kristen Nwanyanwu, MD, MHS, and Fasika A. Woreta, MD, MPH. European Board of Ophthalmology: Peter J. Ringens, MD, PhD, EBO-BCSC Program Liaison, Maastricht, Netherlands; Christina N. Grupcheva, MD, PhD, FEBO, EBO Chair for BCSC Section 1, Dijon, France Financial Disclosures Academy staff members who contributed to the development of this product state that within the 24 months prior to their contributions to this CME activity and for the duration of development, they have had no financial interest in or other relationship with any entity that produces, markets, resells, or distributes health care goods or services consumed by or used in patients, or with any competing commercial product or service. The authors and reviewers state that within the 24 months prior to their contributions to this CME activity and for the duration of development, they have had the following financial relationships:* Dr Bowers: Allergan (S) Dr Browning: Aerpio Therapeutics (S), Alcon Laboratories (S), Alimera Sciences (C), Emmes (S), Genentech (S), Novartis Pharmaceuticals (S), Ohr Pharmaceutical (S), Pfizer (S), Regeneron Pharmaceuticals (S), Springer (P), ZEISS (O) Dr Correa: Castle Biosciences (C) Dr Fintelmann: ALPHAEON CREDIT (O), Strathspey Crown (O) Dr Fouraker: Addition Technology (C, L), Alcon Laboratories (C, L), OASIS Medical (C, L) Dr Goshe: Carl Zeiss Meditec (L) Dr Grosser: InjectSense (O), Ivantis (O) Dr Grupcheva: Allergan (L), Théa (C, L), Johnson & Johnson (L, S) Dr Hardten: Allergan (C, L, S), Avedro (C), Eye Surgical Instruments (C, O), Johnson & Johnson (C), Oculus (L), Optical Systems Design (C, O), TLC Vision (C) Dr Huckfeldt: AGTC (S), MeiraGTx (S), Spark Therapeutics (S) Dr Klapper: AdOM Advanced Optical Technologies (O) Dr Mansberger: Aerie Pharmaceuticals (C), Allergan (S), Bausch + Lomb (C), Envisia Therapeutics (C, S), Gore Medical (C), National Eye Institute (S), Nicox (C) Dr Nwanyanwu: Eyeful LLC (O) Dr Privett: Omeros (O) Dr Radhakrishnan: Netra Systems (C, O) The other authors and reviewers state that within the 24 months prior to their con- tributions to this CME activity and for the duration of development, they have had no financial interest in or other relationship with any entity that produces, markets, resells, or distributes health care goods or services consumed by or used in patients, or with any competing commercial product or service. * C = consultant fee, paid advisory boards, or fees for attending a meeting; E = employed by or re- ceived a W2 from a commercial company; L = lecture fees or honoraria, travel fees or reimbursements when speaking at the invitation of a commercial company; O = equity ownership/stock options in publicly or privately traded firms, excluding mutual funds; P = patents and/or royalties for intellectual property; S = grant support or other financial support to the investigator from all sources, including research support from government agencies, foundations, device manufacturers, and/or pharmaceuti- cal companies Recent Past Faculty A. Jan Berlin, MD Maria Jancevski, MD Jaclyn L. Kovach, MD Maria A. Woodward, MD In addition, the Academy gratefully acknowledges the contributions of numerous past faculty and advisory committee members who have played an important role in the devel- opment of previous editions of the Basic and Clinical Science Course. American Academy of Ophthalmology Staff Dale E. Fajardo, EdD, MBA, Vice President, Education Beth Wilson, Director, Continuing Professional Development Denise Evenson, Director, Brand & Creative Ann McGuire, Acquisitions and Development Manager Stephanie Tanaka, Publications Manager Susan Malloy, Acquisitions Editor and Program Manager Jasmine Chen, Manager of E-Learning Lana Ip, Senior Designer Beth Collins, Medical Editor Eric Gerdes, Interactive Designer Lynda Hanwella, Publications Specialist Debra Marchi, Permissions Assistant American Academy of Ophthalmology 655 Beach Street Box 7424 San Francisco, CA 94120-7424 Contents Introduction to the BCSC...................... xv Objectives............................ 1 1 Using Research to Improve Clinical Practice........ 3 Highlights............................. 3 Researching Answers to Clinical Questions............... 3 Critical Reading of Studies.................... 4 Understanding Study Design..................... 8 Case Reports.......................... 9 Case Series........................... 9 Case-Control Studies....................... 10 Cross-Sectional Studies...................... 12 Cohort Studies......................... 12 Clinical Trials........................... 13 Systematic Reviews and Meta-analyses of Clinical Trials....... 14 Interpreting Diagnostic and Screening Tests.............. 15 The Straightforward Case..................... 15 Complicating Features...................... 16 Summary............................ 21 Discussing Benefits, Risks, Probabilities, and Expected Outcomes With Patients........................... 22 How to Measure and Improve Clinical Practice............. 23 Using Big Data to Improve Clinical Practice............. 23 Issues in Designing a Measurement System............. 24 Implementation of a Monitoring System.............. 25 Analysis of the Results...................... 27 Methods of Presenting Data to Facilitate Continuous Improvement......................... 28 Other Features of Continuous Quality Improvement......... 28 Using Lean Techniques to Improve Clinical Practice......... 31 Summary............................ 32 2 Endocrine Disorders..................... 33 Highlights............................. 33 Diabetes Mellitus.......................... 33 Classification of Diabetes Mellitus................. 33 Diagnosis of Diabetes Mellitus................... 34 Reduction of Risk for Diabetes Mellitus............... 35 Treatment........................... 36 Complications of Diabetes Mellitus................. 38 vii viii  Contents Thyroid Disease........................... 41 Physiology........................... 41 Tests of Thyroid Function..................... 41 Hyperthyroidism........................ 43 Hypothyroidism......................... 44 Thyroiditis........................... 45 Thyroid Tumors......................... 46 Disorders of the Hypothalamic-Pituitary Axis.............. 46 Pituitary Adenomas....................... 47 Pituitary Apoplexy........................ 49 Multiple Endocrine Neoplasia Syndromes............... 49 3 Hypertension......................... 51 Highlights............................. 51 Introduction............................ 51 Classification of Blood Pressure and Diagnosis of Hypertension...... 52 Etiology and Pathogenesis of Hypertension............... 53 Evaluation of Patients With Hypertension............... 55 Treatment of Hypertension...................... 56 Lifestyle Modifications...................... 57 Pharmacologic Treatment..................... 57 Future Treatments and Targets for Hypertension........... 64 Special Considerations........................ 65 Ischemic Heart Disease...................... 65 Heart Failure.......................... 65 Diabetes Mellitus and Hypertension................ 65 Chronic Renal Disease...................... 65 Cerebrovascular Disease..................... 66 Obesity and Metabolic Syndrome................. 66 Obstructive Sleep Apnea Syndrome................ 66 Left Ventricular Hypertrophy................... 66 Peripheral Arterial Disease.................... 66 Orthostatic Hypotension..................... 67 Hypertension in Older Patients.................. 67 Women and Pregnancy...................... 67 Children and Adolescents..................... 68 Withdrawal Syndromes...................... 68 Hypertensive Crisis....................... 69 4 Hyperlipidemia and Cardiovascular Risk......... 71 Highlights............................. 71 Introduction............................ 71 Lipoproteins, Cholesterol, and Cardiovascular Disease.......... 72 Risk Assessment.......................... 72 Management............................ 74 The Role of Statins........................ 76 Metabolic Syndrome....................... 77 Contents d ix 5 Acquired Heart Disease................... 81 Highlights............................. 81 Ischemic Heart Disease....................... 81 Pathophysiology......................... 81 Risk Factors for Coronary Heart Disease.............. 82 Clinical Syndromes....................... 82 Noninvasive Cardiac Diagnostic Procedures............. 86 Invasive Cardiac Diagnostic Procedures.............. 89 Management of Ischemic Heart Disease............... 89 Congestive Heart Failure....................... 95 Classification.......................... 95 Symptoms........................... 95 Clinical Signs.......................... 97 Diagnostic Evaluation...................... 97 Etiology............................ 98 Medical and Nonsurgical Management............... 98 Invasive or Surgical Management................. 100 Disorders of Cardiac Rhythm.................... 101 Bradyarrhythmias and Conduction Disturbances.......... 101 Premature Contractions..................... 101 Tachyarrhythmias....................... 102 6 Cerebrovascular Disease.................. 109 Highlights............................ 109 Introduction........................... 109 Cerebral Ischemia......................... 110 Transient Cerebral Ischemia................... 110 Ischemic Stroke........................ 110 Diagnosis and Management................... 111 Carotid Occlusive Disease...................... 115 Diagnostic Evaluation..................... 116 Management of Carotid Stenosis................. 116 Intracranial Hemorrhage...................... 120 Intracerebral Hemorrhage.................... 120 Intraventricular Hemorrhage.................. 120 Subarachnoid Hemorrhage................... 121 7 Pulmonary Diseases..................... 123 Highlights............................ 123 Introduction........................... 123 Obstructive Lung Diseases..................... 123 Restrictive Lung Diseases...................... 125 Evaluation............................ 125 Treatment............................ 126 Nonpharmacologic Treatment.................. 126 Pharmacologic Treatment.................... 127 x  Contents 8 Hematologic Disorders................... 131 Highlights............................ 131 Blood Composition........................ 131 Erythropoiesis........................... 131 Anemia............................. 132 Anemia Due to Blood Loss or Nutritional Deficiency........ 132 Anemia Due to Defective Hemoglobin Synthesis (Hemoglobinopathies).................... 134 Anemia Due to Destruction of Red Blood Cells.......... 136 Anemia Due to Inflammation and Chronic Disease......... 137 Anemia Due to Bone Marrow Disorders.............. 137 Disorders of Hemostasis...................... 138 Laboratory Evaluation of Hemostasis and Blood Coagulation.... 139 Clinical Manifestations of Hemostatic Abnormalities........ 140 Vascular Disorders....................... 140 Platelet Disorders....................... 141 Disorders of Blood Coagulation................. 144 Primary Hypercoagulable States................. 146 Secondary Hypercoagulable States................ 148 9 Rheumatic Disorders.................... 151 Highlights............................ 151 Introduction........................... 151 Rheumatoid Arthritis....................... 152 Extra-articular Manifestations.................. 152 Laboratory Testing....................... 153 Treatment........................... 153 Spondyloarthritis......................... 154 Ankylosing Spondylitis..................... 154 Reactive Arthritis....................... 155 Enteropathic Arthritis..................... 156 Psoriatic Arthritis....................... 156 Juvenile Idiopathic Arthritis..................... 157 Systemic Lupus Erythematosus................... 158 Signs and Symptoms....................... 158 Diagnosis........................... 160 Treatment........................... 161 Sarcoidosis............................. 162 Signs and Symptoms....................... 162 Diagnosis........................... 162 Treatment........................... 163 Antiphospholipid Syndrome.................... 163 Signs and Symptoms....................... 163 Diagnosis........................... 163 Treatment........................... 164 Systemic Sclerosis.......................... 164 Signs and Symptoms...................... 164 Contents d xi Diagnosis........................... 165 Treatment........................... 165 Sjögren Syndrome......................... 166 Polymyositis and Dermatomyositis.................. 167 Polymyalgia Rheumatica...................... 168 Relapsing Polychondritis...................... 168 Vasculitis............................. 169 Large-Vessel Vasculitis..................... 170 Medium-Sized–Vessel Vasculitis................. 170 Small-Vessel Vasculitis..................... 171 Variable-Vessel Vasculitis.................... 173 Medical Therapy for Rheumatic Disorders.............. 174 Corticosteroids........................ 174 Nonsteroidal Anti-inflammatory Drugs.............. 176 Disease-Modifying Antirheumatic Drugs............. 176 10 Geriatrics........................... 183 Highlights............................ 183 Introduction........................... 183 Physiologic Aging and Pathologic Findings of the Aging Eye....... 184 Elder Abuse............................ 185 Perioperative Considerations in the Management of Elderly Patients... 187 Psychology of Aging........................ 188 Depression.......................... 188 Alzheimer Disease and Dementia................ 190 Osteoporosis........................... 190 Falls............................... 191 11 Behavioral and Neurologic Disorders........... 193 Highlights............................ 193 Introduction........................... 193 Behavioral Disorders........................ 194 Behavioral Disorders Associated With Medical Conditions..... 194 Schizophrenia......................... 194 Mood Disorders........................ 195 Somatization, Anxiety, and Stress-Related Disorders........ 196 Substance Abuse Disorders................... 198 Pharmacologic Treatment of Psychiatric Disorders........... 199 Antipsychotic Drugs...................... 199 Antianxiety and Hypnotic Drugs................. 201 Neurologic Disorders........................ 204 Parkinson Disease....................... 204 Multiple Sclerosis....................... 206 Epilepsy............................ 206 Stroke............................ 209 Alzheimer Disease and Dementia................ 209 Prion-Associated Neurologic Disorders.............. 211 Informed Consent in Patients with Behavioral and Neurologic Disorders.......................... 211 xii  Contents 12 Preventive Medicine..................... 213 Highlights............................ 213 Screening Procedures....................... 213 Cardiovascular Diseases..................... 214 Cancer............................ 215 Infectious Diseases....................... 222 Immunization........................... 223 Hepatitis........................... 224 Influenza.......................... 226 Varicella-Zoster........................ 227 Measles............................ 228 Mumps............................ 228 Rubella............................ 229 Polio............................. 229 Tetanus and Diphtheria..................... 229 Rotavirus........................... 230 Pneumococcal Pneumonia................... 230 Meningococcus........................ 231 Human Papillomavirus..................... 231 Travel Immunizations...................... 232 New and F uture Vaccines.................... 232 13 Cancer............................. 235 Highlights............................ 235 Introduction........................... 235 Etiology............................. 235 Radiation Therapy......................... 237 Chemotherapy.......................... 239 Angiogenesis Inhibitors....................... 241 Biologic Therapies......................... 241 14 Infectious Diseases..................... 245 Highlights............................ 245 General Microbiology....................... 245 Staphylococcus........................... 246 Streptococcus........................... 247 Clostridium difficile........................ 249 Haemophilus influenzae....................... 249 Neisseria............................ 250 Pseudomonas aeruginosa...................... 251 Treponema pallidum........................ 252 Diagnosis........................... 252 Management......................... 253 Borrelia burgdorferi........................ 254 Stages............................. 254 Diagnosis........................... 254 Management......................... 255 Contents d xiii Chlamydia trachomatis....................... 255 Mycoplasma pneumoniae...................... 256 Mycobacteria.......................... 256 Tuberculosis.......................... 256 Fungal Infections......................... 258 Toxoplasma............................ 258 Herpesvirus............................ 259 Herpes Simplex........................ 260 Varicella-Zoster........................ 260 Cytomegalovirus........................ 261 Epstein-Barr Virus....................... 262 Influenza............................. 262 Hepatitis............................. 262 Hepatitis A and B....................... 262 Hepatitis C and Other Forms of Hepatitis............. 263 Human Papillomavirus....................... 264 Ebola Virus............................ 264 Zika Virus............................ 265 Human Immunodeficiency Virus.................. 266 Etiology and Pathogenesis.................... 266 Clinical Syndromes....................... 267 Diagnosis........................... 267 Treatment........................... 268 Immune Reconstitution Inflammatory Syndrome.......... 269 Update on Antibiotics....................... 270 Antibacterial Agents...................... 270 Future Directions....................... 276 Antifungal Agents....................... 277 Antiviral Agents........................ 277 COVID-19............................ 279 15 Perioperative Management in Ocular Surgery...... 281 Highlights............................ 281 Introduction........................... 281 Preoperative Assessment...................... 281 Children and Adolescents.................... 283 Management of Medical Conditions Associated with Increased Perioperative Risk........................ 283 Cardiovascular Disease..................... 283 Diabetes Mellitus........................ 284 Respiratory Diseases...................... 284 Perioperative Medication Management................ 285 Cardiac............................ 285 Diabetes Mellitus........................ 286 Pulmonary Medications..................... 287 Perioperative Considerations.................... 287 Preoperative Fasting...................... 287 xiv  Contents Latex Allergy......................... 288 Universal Protocol....................... 288 Intraoperative Considerations.................... 289 Systemic Anesthetic Agents................... 289 Local Anesthetic Agents..................... 290 Malignant Hyperthermia.................... 291 16 Medical Emergencies and Ocular Adverse Effects of Systemic Medications.................. 295 Highlights............................ 295 Introduction........................... 295 Cardiopulmonary Arrest...................... 296 Syncope............................. 299 Hypoglycemia........................... 300 Shock.............................. 300 Classification......................... 300 Assessment.......................... 301 Treatment........................... 301 Anaphylaxis.......................... 302 Seizures and Status Epilepticus................... 303 Toxic Reactions to Local Anesthetic Agents and Other Drugs...... 304 The Opioid Crisis....................... 306 Ocular Adverse Effects of Systemic Medications............ 307 17 Social Determinants of Health............... 311 Highlights............................ 311 Introduction........................... 311 Categories of Social Determinants of Health.............. 311 Health Care Access and Quality................. 312 Economic Stability....................... 313 Education Access and Quality.................. 313 Neighborhood and Built Environment.............. 314 Social and Community Context................. 314 Discrimination and Social Determinants of Health........... 314 Ethnicity........................... 315 Gender............................ 315 Sexual Orientation and Gender Identity.............. 315 Age and Disability....................... 315 Approaches to Address Social Determinants of Health......... 316 Basic Texts............................ 317 Related Academy Materials..................... 319 Requesting Continuing Medical Education Credit........... 321 Study Questions.......................... 323 Answer Sheet for Section 1 Study Questions.............. 331 Answers............................. 333 Index.............................. 341 Introduction to the BCSC The Basic and Clinical Science Course (BCSC) is designed to meet the needs of residents and practitioners for a comprehensive yet concise curriculum of the field of ophthalmol- ogy. The BCSC has developed from its original brief outline format, which relied heavily on outside readings, to a more convenient and educationally useful self-contained text. The Academy updates and revises the course annually, with the goals of integrating the basic sci- ence and clinical practice of ophthalmology and of keeping ophthalmologists current with new developments in the various subspecialties. To address a particularly important and timely issue, Chapter 17, Social Determinants of Health, has been added to Section 1. This is a preview of the chapter on this topic that will appear in the 2023–2024 major revision. The BCSC incorporates the effort and expertise of more than 100 ophthalmologists, organized into 13 Section faculties, working with Academy editorial staff. In addition, the course continues to benefit from many lasting contributions made by the faculties of previous editions. Members of the Academy Practicing Ophthalmologists Advisory Com- mittee for Education, Committee on Aging, and Vision Rehabilitation Committee review every volume before major revisions. Members of the European Board of Ophthalmology, organized into Section faculties, also review each volume before major revisions, focusing primarily on differences between American and European ophthalmology practice. Organization of the Course The Basic and Clinical Science Course comprises 13 volumes, incorporating fundamental ophthalmic knowledge, subspecialty areas, and special topics: 1 Update on General Medicine 2 Fundamentals and Principles of Ophthalmology 3 Clinical Optics and Vision Rehabilitation 4 Ophthalmic Pathology and Intraocular Tumors 5 Neuro-Ophthalmology 6 Pediatric Ophthalmology and Strabismus 7 Oculofacial Plastic and Orbital Surgery 8 External Disease and Cornea 9 Uveitis and Ocular Inflammation 10 Glaucoma 11 Lens and Cataract 12 Retina and Vitreous 13 Refractive Surgery References Readers who wish to explore specific topics in greater detail may consult the references cited within each chapter and listed in the Basic Texts section at the back of the book. xv xvi  Introduction to the BCSC These references are intended to be selective rather than exhaustive, chosen by the BCSC faculty as being important, current, and readily available to residents and practitioners. Multimedia This edition of Section 1, Update on General Medicine, includes videos related to top- ics covered in the book. Selected by members of the BCSC faculty to present important topics that are best delivered visually, the videos are available to readers of the print and electronic versions of Section 1 (www.aao.org/bcscvideo_section01). Mobile-device users can scan the QR code below (a QR-code reader may need to be installed on the device) to access the video content. Self-Assessment and CME Credit Each volume of the BCSC is designed as an independent study activity for ophthalmology residents and practitioners. The learning objectives for this volume are given on page 1. The text, illustrations, and references provide the information necessary to achieve the objectives; the study questions allow readers to test their understanding of the material and their mastery of the objectives. Physicians who wish to claim CME credit for this educational activity may do so online by following the instructions at the end of the book.* Conclusion The Basic and Clinical Science Course has expanded greatly over the years, with the ad- dition of much new text, numerous illustrations, and video content. Recent editions have sought to place greater emphasis on clinical applicability while maintaining a solid foun- dation in basic science. As with any educational program, it reflects the experience of its authors. As its faculties change and medicine progresses, new viewpoints emerge on controversial subjects and techniques. Not all alternate approaches can be included in this series; as with any educational endeavor, the learner should seek additional sources, including Academy Preferred Practice Pattern Guidelines. The BCSC faculty and staff continually strive to improve the educational usefulness of the course; you, the reader, can contribute to this ongoing process. If you have any sugges- tions or questions about the series, please do not hesitate to contact the faculty or the editors. The authors, editors, and reviewers hope that your study of the BCSC will be of last- ing value and that each Section will serve as a practical resource for quality patient care. * This activity meets the Self-Assessment CME requirements defined by the American Board of Oph- thalmology (ABO). Please be advised that the ABO is not an accrediting body for purposes of any CME program. ABO does not sponsor this or any outside activity, and ABO does not endorse any particular CME activity. Complete information regarding the ABO Self-Assessment CME Maintenance of Certifi- cation requirements is available at https://abop.org/maintain-certification/cme-self-assessment/. Objectives Upon completion of BCSC Section 1, Update on General Medicine, the reader should be able to describe the various f actors to consider in critically reviewing clinical research explain the importance of the randomized, controlled clinical study in evaluating the effects of new treatments describe the classification, pathophysiology, and presentation of diabetes mellitus, as well as the diagnostic criteria for this disease describe the various therapeutic approaches for diabetes mellitus classify the levels of hypertension based on blood pressure measurements list the major classes of antihypertensive medications, their characteristics, and their adverse effects discuss the indications for dietary and pharmacologic treatment of hyperlipidemia describe the various diagnostic procedures used in the evaluation of patients with coronary heart disease state the current treatment options for ischemic heart disease, heart failure, and cardiac arrhythmias list the common causes of stroke distinguish between obstructive and restrictive, reversible and irreversible, pulmonary diseases, and give examples of each type discuss the major behavioral disorders and possible therapeutic modalities for these conditions (including the ocular adverse effects of psychoactive medications) list some of the factors associated with a patient’s adherence or nonadherence to medical regimens explain the rationale for and value of screening programs for various systemic diseases discuss the major disease processes affecting most of the adult population, and briefly explain how preventive measures may reduce the morbidity and mortality that these diseases cause list the most prevalent types of cancer for men and for women together with the appropriate screening methods for detecting them describe current concepts about the etiologies of most malignancies describe traditional as well as more novel approaches to the treatment of various types of cancer describe the ophthalmic manifestations of the major systemic diseases covered in this volume list the most common h uman pathogens and their manifestations discuss the epidemiology, clinical features, and treatment of HIV infection list the newer antiviral, antifungal, and antibacterial agents and their benefits and adverse effects describe the early manifestations and treatment of malignant hyperthermia describe the current American Heart Association guidelines for performing cardiopulmonary resuscitation discuss the impact of social determinants of health on patient wellness CHAPTER 1 Using Research to Improve Clinical Practice Highlights Research can help answer important clinical questions such as the utility of diagnos- tic and screening tests or the benefits, risks, probabilities, and expected outcomes of surgeries. It is important for clinicians to understand how to measure and compare their clini- cal practice and how to present data to demonstrate improved clinical practice. The use of big data (eg, the IRIS program) or the lean technique can improve clini- cal outcomes, efficiency, and patient satisfaction. Ophthalmologists use clinical research to establish best practices for patient care. This chapter will help the clinician understand how to critically review research and apply the results to the clinical practice of ophthalmology. Researching Answers to Clinical Questions Formulating the clinical question is the first step in resolving a diagnostic or management issue. Examples of clinical questions in ophthalmology include: What are the results of minimally invasive glaucoma surgeries in patients with low-pressure glaucoma versus higher-pressure glaucoma? Do racial and ethnic minority populations in the United States have a higher risk of proliferative vitreoretinopathy a fter pars plana vitrectomy? What is the expected survival of an endothelial graft in a patient with Fuchs dystrophy? Clinicians can use various sources of information to research their answers to ques- tions, including general textbooks on ophthalmology, review journals on specific sub- jects (eg, Survey of Ophthalmology [www.surveyophthalmol.com]), and educational material from the American Academy of Ophthalmology ([AAO]; www.aao.org/clinical -education) (eg, Preferred Practice Pattern guidelines, Focal Points modules). In addi- tion, clinicians can use the Cochrane Library (www.cochranelibrary.com) to access high- quality meta-analyses regarding specific management issues (eg, surgery for nonarteritic ischemic optic neuropathy, intervention for involutional lower-eyelid ectropion). PubMed (https://pubmed.ncbi.nlm.nih.gov) is another g reat resource for primary sources of information. Clinicians with more specific questions or who are looking for specific data 3 4 Update on General Medicine can narrow their search to the most applicable articles. PubMed provides detailed instruc- tions on using appropriate keywords such as type of study: from laboratory-based studies of basic science (eg, cell culture, molecular biology) to animal studies (eg, testing of new drugs or specific surgical techniques) to clinical studies (eg, case reports, case series, randomized controlled trials). Critical Reading of Studies Before committing time to reading a published study, the clinician should review its ab- stract to ascertain whether the study addresses the question of interest. After reviewing the abstract, the clinician should read the rest of the study critically to determine the characteristics of the study population, recruitment strategy, sample size, intervention, outcomes of interest, and statistical methods used, and thus evaluate whether the study is valid and applicable to the clinical question. Are the study population and recruitment strategy applicable to my patients? Understanding a study’s population and its recruitment strategy is key to understanding the setting of the study. Was the trial clinic-based, multicenter, or community-based? In therapeutic trials, the inclusion and exclusion criteria describe the characteristics of those who were or were not treated with an intervention. Specific patient groups may have been excluded because they were considered a vulnerable population. For example, most trials of ocular hypotensive drugs exclude children and pregnant women; as a re- sult, there are minimal data on the safety and efficacy of most ocular hypotensive agents in these 2 groups of patients. Thus, if a clinician wants to do research before deciding whether to use a specific ocular hypotensive agent in a pregnant woman or in a child, most of the evidence can be found only in individual case reports or retrospective case series. The next step in evaluating a study is exploring whether the study created selection bias by assigning the intervention to certain participants. Was the intervention randomly assigned? Was the treated group comparable to the control group? The purpose of ran- domly assigning an intervention to participants is to minimize bias on the part of the investigators and the patient. For example, an investigator may create selection bias by inadvertently enrolling less complex patients for a new surgery, potentially biasing their outcomes t oward better results. Whether the selection was biased or random can be determined by examining w hether the participants assigned to each group are similar in the characteristics that may affect the outcome of interest. For example, when evaluating a study assessing the effect of laser treatment versus anti–vascular endothelial growth factor (anti-VEGF) treatment on dia- betic retinopathy, the clinician should examine whether patients’ hemoglobin A1c levels, blood pressure, and severity of disease are similar between study groups, because these factors may alter the progression of retinopathy. Use of a control group is also important because it indicates whether the results of the intervention are above and beyond benefi- cial effects of participants’ enrollment in a trial, which usually includes selected, motivated patients. Chapter 1: Using Research to Improve Clinical Practice 5 Clinical trials may study a narrow subset of a disease, making the results applicable and generalizable only to similar patients. A common error is extrapolating such data to apply to all patients or varying degrees of disease severity. For example, if a treatment is successful only in patients with mild glaucomatous damage who underwent trabeculec- tomy but not in those with advanced glaucomatous damage, the study results should be applied only to similar patients—in this case, patients with mild glaucomatous damage. Was the sample large enough to detect a difference? The sample size must have enough power to reject the null hypothesis, which states that there is no difference (in the outcome of interest) in the group that received the intervention compared with the group that did not receive the intervention. A study must have enough power to reject the null hypothesis. When this occurs, it suggests support for the “alterna- tive hypothesis,” which states that a true difference exists between the groups. Power de- pends on the sample size (number of participants), the expected difference in the outcome of interest in the intervention group compared with the control group (eg, improvement in visual acuity, resolution of macular edema), and the variability (eg, standard deviation) of the outcome of interest. In general, an intervention with a larger treatment effect and smaller variability requires a smaller sample size. These characteristics should be reported in the Methods section of the study. Are the treatments and outcomes clinically relevant? The clinician should ascertain w hether the study’s results can be applied to his or her pa- tients. Questions to consider include the following: Is the intervention available and applicable to the current practice environment? Are the outcomes clinically important? Are all clinically important outcomes evaluated? Is the treatment difference clinically significant? It is important to consider whether the intervention is useful in practice. It may be too expensive, too difficult to perform, or no longer in general use. If so, the study may pose little benefit to current clinical care. Is the intervention reproducible? The study should describe the intervention in enough detail to allow the experiment to be replicated. For example, a surgical study should explain all the steps of the procedure so that different surgeons are able to perform the procedure in the same manner in each case. Did all surgeons involved in the study perform it similarly, and were their results similar? Did the study include a training session before the start of the study, monitor specific aspects of the surgical procedure, and standardize postoperative care? In general, a study should avoid differences in study procedures except for the intervention of interest. In ad- dition, to decrease the risk of investigator bias, the study should try to mask the observer to the intervention. Investigator bias may occur when the investigator expects a different result in the intervention group and adjusts his or her measurement of the outcome of interest to satisfy this expectation. 6 Update on General Medicine Is the outcome clearly defined and reliable? The study should clearly state the primary and secondary outcomes of interest as well as the expected change for these outcomes. For example, if the primary outcome is improvement in visual acuity, the study should indicate the logMAR value that represents improve- ment, the range, the distribution of results (eg, normal, skewed to the right or left), and the variability. These statements allow the reader to determine w hether the study was able to prove or disprove the null hypothesis. Many outcomes (eg, visual acuity, intraocular pressure [IOP], macular thickness as measured with optical coherence tomography [OCT]) will have measurement error. This measurement error will increase the variability of the outcome of interest or create a dif- ference in results when no true difference in outcomes exists. Therefore, a study should standardize measurement of the outcome of interest for all investigators. For example, the Ocular Hypertension Treatment Study created a standardized method to check IOP. The “recorder” placed the tonometry dial at 20 mm Hg while an “observer” measured the IOP and adjusted the dial to the intersection of the tonometry mires without viewing the dial. Finally, the recorder recorded the IOP measurement and changed the dial back to 20 mm Hg, then repeated the measurement sequence. The sequence was repeated a third time if the measurements differed by 2 mm Hg. By using a masked recorder and observer, and repeating the testing, the study created a standardized method intended to decrease mea surement error and the variability of IOP measurement. Was the follow-up time and reporting long enough? The validity of a study is anchored on (1) adequate duration of follow-up and (2) follow- up of all participants. Thus, in evaluating a study, the clinician should look for how many of the participants completed follow-up and w hether the study reported outcomes for all participants. For example, in a study assessing the use of atropine eyedrops versus patching for treatment of amblyopia, a follow-up of 3–6 months may be adequate; similar follow-up periods may be appropriate for tracking macular edema resolution a fter l aser or drug ther- apy or monitoring visual acuity improvement after cataract extraction. Conversely, glau- coma progresses over long periods; therefore, trials assessing visual field loss in glaucoma would require longer follow-up, such as 5 years. Consequently, the typical rate of disease progression is an important guide in establishing the duration of follow-up required. Finally, the study should report the results for all participants, which is called an “in- tention to treat” analysis. The study should state the reasons for loss to follow-up, and any differences in reasons between the study groups. For example, participants in the in- tervention group of a drug trial may be more likely to drop out than t hose in the placebo group if they experience ocular adverse effects from the drug, such as burning or stinging. Is the analysis appropriate for the outcome? Statistical tests depend on the type of data used to determine the difference between 2 treatment groups. For example, if the data are normally distributed (ie, parametric, con- forming more or less to a bell-shaped curve) and are continuous (eg, age), then a t test comparing the intervention and control groups can be performed. For continuous data that are not normally distributed, researchers can use nonparametric tests such as the Chapter 1: Using Research to Improve Clinical Practice 7 Mann-Whitney U test or the Wilcoxon signed rank test. For categorical data (present or absent; small, medium, or large), the study may use a chi-square test. All of these tests provide a P value, which is a number that indicates the likelihood that a difference be- tween the 2 groups is due to chance alone. For example, a P value of 2 groups 1-way ANOVA Kruskal-Wallis test Continuous Pearson corr / Linear reg Spearman corr / Linear reg 1 group Chi-square test / Fisher exact test Paired McNemar test / Kappa statistic Outcome Categorical variable ≥2 groups Chi-square test / Fisher exact test / Logistic regression Continuous Logistic regression / Sensitivity & specificity / ROC curve ≥2 groups Kaplan-Meier method plot with log-rank test Survival Continuous Cox regression Figure 1-1 Flow chart of commonly used statistical tests. ANOVA = analysis of variance; Cox regression = Cox proportional hazards regression model; Linear reg = linear regression; Pearson corr = Pearson product moment correlation; ROC = receiver operating characteristic; Spearman corr = Spearman rank correlation. See also Figure 1-8, which shows examples of histograms with normal and skewed data distributions. 8 Update on General Medicine motivate them to make decisions that benefit the entity. An example of a COI would be if a person who was a paid speaker for an entity wrote and published a paper describing that entity’s new device and its benefits. B ecause of the relationship between the author and the entity, there is a risk that the COI could positively influence the author’s decision-making in the entity’s favor. If the author of the paper biases the study results to describe large benefits for the device with minimal risk, the author may secondarily benefit by receiving more paid speaking engagements from the entity. Although this COI and the author’s role in the paper may not represent an impro- priety, such an impropriety is one reason that medical journals require authors and other decision makers to disclose any COIs. Secondarily and most importantly, medical jour- nals also require the author and other individuals with COIs to present an accurate and balanced assessment of the benefits and all of the risks of the drug or new device. Even if their motivations do not include a direct financial benefit in the form of COI, all authors are motivated to publish their findings in research journals, for reasons that may include academic promotion, future research grants, and their national reputation. Overall, any research should include an accurate and balanced assessment of the results regardless of whether the authors have COI, and readers should use their best judgment about w hether the research includes a balanced presentation of the results. Understanding Study Design Clinical research uses a wide array of study designs. In observational studies, also known as nonexperimental studies, investigators evaluate characteristics, behaviors, and exposures in participants with a particular disease, condition, or complication. An observational study reports only the characteristics of the study population; it does not directly manipu- late behaviors (eg, cigarette smoking) or exposures (eg, use of a medication, laser treat- ment). In experimental studies, typically clinical t rials, subjects are assigned to a particular treatment, such as a prescribed behavior (eg, eating a diet high in antioxidant foods), or a therapeutic or preventive intervention (eg, use of an oral neuroprotective agent for patients with glaucoma, antioxidant vitamin supplementation for patients with early age-related macular degeneration [AMD]). When conducted and interpreted appropriately, each type of study design may pro- vide valuable information. Researchers employ observational studies when describing the presentation and progression of disease, generating hypotheses, and efficiently assessing data that may already exist for testing a hypothesis about an intervention. Examples of observational studies include case reports, case series, case-control studies, cross-sectional studies, and cohort studies. In contrast, prospective randomized controlled trials provide the best evidence regarding the effects of an intervention. Finally, meta-analyses provide a methodology to summarize the results of multiple clinical trials addressing similar research questions. Figure 1-2 depicts the levels of evidence that can be obtained from different study designs; note that meta-analyses and controlled trials offer the highest levels of evidence. Chapter 1: Using Research to Improve Clinical Practice 9 Systematic reviews Randomized and meta-analyses controlled double- masked studies Cohort studies Case-control studies Case series Case reports Figure 1-2 The pyramid of evidence, which illustrates the relative strength of different study designs. (Adapted with permission from Medical Research Library of Brooklyn. Guide to Research Methods: The Evi- dence Pyramid. EBM Tutorial. https://library.downstate.edu/evidence-based-medicine.html.) Case Reports A case report describes a finding in regard to a single patient to alert readers to a rare condition or unusual treatment result. For example, in 2005, Friedman reported retinal vasculitis in an apparently healthy patient with none of the common causes of vasculitis, such as toxoplasmosis, syphilis, Behçet disease, sarcoidosis, lupus, or herpes. A magnetic resonance imaging (MRI) scan of the patient’s brain revealed findings typical of multiple sclerosis (MS). Although clinicians recognize that retinal vasculitis develops in MS pa- tients, this study was the first to report retinal vasculitis as the initial presentation of MS. This case report demonstrated that clinicians should consider MS when they have tested for more common c auses of vasculitis, but the etiology remains unclear. Case reports cannot provide information on treatment efficacy or assert w hether a disease is caused by an exposure. At most, they can suggest a previously unsuspected find- ing or mechanism of disease. Friedman SM. Retinal vasculitis as the initial presentation of multiple sclerosis. Retina. 2005;25(2):218–219. Case Series Case series investigate the presentation, history, and/or follow-up of a group of patients and provide valuable information on the natural history or prognosis of a disease. Case series may differ from clinical t rials in regard to patient selection, patient characteristics, and length and completeness of follow-up; t hese characteristics may establish the quality and applicability of a case series. The case series provides preliminary information for a larger study with a comparison group. Case series can include bias if they only include patients with severe disease from tertiary referral centers such as university-based clinics, or patients with only mild cases of a disease. For example, a study examining a new minimally invasive glaucoma surgery in patients with glaucoma may show incremental lowering of IOP and the need for fewer 10 Update on General Medicine medications 6 months after the surgery. However, in the Methods section of the study, the reader discovers that the study population came from a tertiary glaucoma center that specialized in a new procedure to reduce patient dependence on drops. Also, the study only included patients with stable glaucoma. In other words, the study was biased toward patients with mild disease and was therefore not generalizable to patients with other se- verities of glaucoma; it was also biased to decrease the number of medications b ecause the providers and patients involved in the study were motivated to decrease or stop their glaucoma drops after the procedure. Case series might not standardize the collection of patient information, measure ments, tests, and other evaluations. This may result in underreporting or overreporting of results. For example, the technicians, examination rooms, lighting, and charts used to measure visual acuity may differ within the various clinics. Or study personnel may re cord visual acuity differently; for example, some may record the nearest w hole line (20/25) while others record to the letter (20/25 + 2). Lengths of follow-up intervals may vary within a single case series. If there are differ- ences in follow-up time, the study should report what the specific follow-up times were, such as 1, 2, and 3 years after the initiation of treatment. When the outcome being measured is an event, such as corneal graft failure, a survival analysis can account for the varying lengths of follow-up. If the study does not follow all of its participants for the full length of the possible follow-up period, these losses to follow-up may cause the reported out- look for the case series to be biased. For example, in a case series of patients with macu- lar edema from branch retinal vein occlusion, some patients may choose not to return because their macular edema has resolved, and their vision has improved; some patients may experience further loss of vision and seek care from another ophthalmologist; and some patients may move to another location. Overall, if a large percentage of patients do not return for complete follow-up, the study results may not be valid; the remaining sub- jects may have had an unusually good or unusually bad course compared with the subjects lost to follow-up. Case-Control Studies Figure 1-3 illustrates the structure of case-control studies. Case-control studies investigate a hypothesis about an association between exposures or potential risk f actors (eg, smoking, medical conditions, therapies) and outcomes of interest (eg, loss of visual acuity, develop- ment of glaucoma, corneal graft failure, complications of cataract surgery). Case-control studies select a group of participants with the disease of interest (cases) and a group of comparable individuals who are free of disease (controls). Each study compares the past exposures and characteristics of the 2 groups to determine whether differences exist be- tween the groups. If so, the study w ill conclude that the exposures or characteristics that differ are associated with the disease. Researchers select cases and controls from a current database and obtain the history of exposures through patient surveys and/or review of medical records. Thus, research- ers can perform case-control studies more quickly and inexpensively than cohort studies (discussed later in the chapter), b ecause cohort studies require extra time and money to Chapter 1: Using Research to Improve Clinical Practice 11 Case-control study Obtain history Determine if risk Identify cases factor/exposure is present Compare proportions with exposure Obtain history Determine if risk Identify controls factor/exposure is present Cohort study All disease-free Identify those Follow-up Determine with exposure/risk factor disease status Compare proportions with disease Identify those Follow-up Determine without exposure/risk factor disease status Figure 1-3 Simplified schematics of observational study designs. follow participants. During record reviews or patient interviews, case-control studies can collect data on many potential risk factors simultaneously. However, exposure data may be less accurate in case-control studies than in cohort studies. For example, patients with retinal vein occlusion (cases) may be more likely than control patients to recall taking medications (eg, aspirin) in the past because control pa- tients, who do not have the disease, may be less motivated to scrutinize their past behavior. Therefore, a higher proportion of cases than controls might report use of aspirin in the past 6 months, even if in truth the proportion of aspirin users was the same in both cases and controls. This recall bias in cases may strengthen the association between aspirin use and vein occlusion. Case-control studies may be subject to selection bias if they do not have an appropri- ate control group. For example, a study may show that myopia offers a protective effect on 12 Update on General Medicine retinal vein occlusion if the study collects its cases from a retinal group but collects its controls from a general ophthalmology practice that offers refractive surgery for myopia. The proportion of individuals with myopia would be smaller among the cases (from the retin al group) than among the controls (from the general practice). The study may con- clude that myopia is protective against retinal vein occlusion, but the apparent association would actually be attributable to selection bias. To learn more about other sources of bias, an interested reader may consult general epidemiology textbooks, such as the following. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd, mid-cycle revision ed. Philadelphia: Lippincott Williams & Wilkins; 2012. Cross-Sectional Studies Cross-sectional studies correlate exposures and risk factors with the presence of disease without the benefit of knowing the timing or sequence of exposure and disease develop- ment. An example of a cross-sectional study is one in which a researcher collects a blood sample from patients and records their lens status (phakic, pseudophakic, or aphakic) at the same time. The study could evaluate the association between a history of cataract surgery (case status) and cholesterol level and gender (potential risk factors). However, if the mean cholesterol level is higher in cases than in t hose without a history of cataract surgery, the researcher would not know whether the elevated cholesterol level occurred before cataract surgery. With this study design, it is also important to consider w hether a confounding factor may be affecting the association. For this study, age could be a con- founding factor, because cholesterol levels increase with age, as does the likelihood of cataract surgery. The researcher could use data analysis tools such as stratification and/or regression analysis to adjust for age and then determine w hether the cholesterol–cataract surgery association is still present in each of the age strata. Cohort Studies Researchers may use cohort, or follow-up, studies to investigate the association between exposures or potential risk factors and patient outcomes. These studies identify subjects who are free of the disease of interest and classify them by the presence or absence of po- tential risk factors. Then the study follows t hese subjects for subsequent development of the disease of interest (see Fig 1-3). The Los Angeles Latino Eye Study (LALES) is an example of a population-based cohort study with prospective data collection. This study examined and interviewed ap- proximately 6000 residents of Los Angeles, California, and followed them longitudinally for the incidence of ocular disease. Researchers explored potential risk factors for diseases such as AMD, diabetic retinopathy, glaucoma, and cataract using the residents’ exposures at the beginning of the study and the incidence of the diseases years later. For example, the investigators discovered new cases of macular degeneration over a 4-year period in Latino individuals. The study found that older age and pulse pressure (difference be- tween systolic and diastolic pressure) w ere independently associated with new onset early AMD, soft indistinct drusen, and retinal pigmentary abnormalities. This is an example of Chapter 1: Using Research to Improve Clinical Practice 13 prospectively assessing the risk factor (blood pressure and age) for an outcome of interest (incidence of AMD). Cohort studies can provide associations between risk factors and disease. The pri- mary weakness of this study design is that participants with the risk f actor of interest may differ in many ways from those without the risk factor, and those other characteristics may affect the incidence of the disease. One example relates to the higher incidence of graft failure among patients with interrupted sutures. It would be inaccurate to conclude that use of interrupted sutures increases the risk of graft failure, because ophthalmologists use interrupted sutures in patients with a preexisting risk of graft failure, such as stromal vascularization. In this example, stromal vascularization is a confounding f actor. Statisti- cal analysis techniques, such as stratified analysis and regression analysis, can adjust for the effect of known confounding f actors. However, quite often investigators do not under- stand all the factors that affect the incidence of a disease. For this reason, cohort studies may identify associations and disease incidence, but these associations are not considered causal. Choudhury F, Varma R, McKean-Cowdin R, Klein R, Azen SP; Los Angeles Latino Eye Study Group. Risk factors for four-year incidence and progression of age-related macular degeneration: the Los Angeles Latino Eye Study. Am J Ophthalmol. 2011;152(3):385–395. Clinical Trials Figure 1-4 demonstrates the major difference between clinical trials and cohort studies: clinical trials randomly assign patients to different treatment groups (exposure groups). Random assignment yields treatment groups with similar characteristics in regard to vari- ables that may alter outcomes or the risk of complications from the treatment. This control of confounding factors is a major advantage of clinical trials over other study designs. Study population Determine Treatment A disease status Compare Random proportions assignment with disease Determine Treatment B disease status Figure 1-4 Simplified schematic of a randomized controlled trial. 14 Update on General Medicine All the previously mentioned features of high-quality observational studies, such as the following, should also be applied to randomized controlled trials: a well-defined research question and objectives explicit inclusion and exclusion criteria an adequate sample size standardized procedures predefined, objective primary and secondary outcomes masking of patients, treating clinicians, and evaluators to the assigned treatment complete follow-up of all patients The CONSORT (Consolidated Standards of Reporting Trials) Statement, an evidence- based set of recommendations, includes a checklist of features that should be included in the design and reporting of clinical trials. When evaluating a clinical trial, the clinician should consider 2 issues in addition to the other features of high-quality studies. The first is w hether the study excluded patients from data analysis b ecause they did not meet all of the eligibility criteria, experienced ad- verse effects and stopped treatment, or did not adhere to the treatment regimen. Exclusion of these types of patients creates biased results b ecause the excluded patients’ results may differ from those of the patients included in the analysis. For this reason, clinical trials should include an intention-to-treat analysis, which includes the data from all enrolled participants, and separate analyses of those who completed the trial and those who did not. Results from subgroups of patients (eg, young vs old, hypertensive vs nonhyperten- sive) should be regarded with suspicion. By statistical chance alone, a study can identify a subgroup of patients for whom the benefit of treatment is statistically significant. A subgroup evaluation may be considered valid if the investigators identified the subgroup a priori in the study design, treatment results vary similarly across subgroups (eg, success steadily decreases in each age stratum as the participants become younger), and a biologi- cally plausible explanation exists for the finding. Systematic Reviews and Meta-analyses of Clinical Trials Because they combine evidence from 2 or more clinical trials, systematic reviews and meta-analyses provide the strongest evidence for assessing interventions for a particular condition (see Fig 1-2). For example, to compare the safety and efficacy of intracameral cefu- roxime, moxifloxacin, and vancomycin at the end of cataract surgery, Bowen and colleagues reviewed the results of 17 studies with over 900,000 eyes. They showed an 80% decrease (P <.001) in risk of endophthalmitis when using intracameral antibiotics. They also re- ported minimal toxicity for moxifloxacin; dosing errors related to toxicity for cefuroxime; and rare toxic retinal events with vancomycin use. Overall, this meta-analysis strongly supports intracameral antibiotics after cataract surgery to prevent endophthalmitis. Bowen RC, Zhou AX, Bondalapati S, et al. Comparative analysis of the safety and efficacy of intracameral cefuroxime, moxifloxacin and vancomycin at the end of cataract surgery: a meta-analysis. Br J Ophthalmol. 2018;102(9):1268–1276. Chapter 1: Using Research to Improve Clinical Practice 15 Interpreting Diagnostic and Screening Tests The goal of this section is to help the reader interpret diagnostic and screening tests. The first example presents a relatively straightforward case; it involves a screening test with a binary (yes/no) outcome, a disease that the patient either has or does not have, and a pa- tient about whom nothing is known at the time of screening. The subsequent discussions examine complicating features that often occur in ophthalmic practice and in research. The reader should consider these complicating features when evaluating results of diag- nostic and screening tests. The Straightforward Case A fictitious study evaluates use of a simple, quick strabismus test in 100 children, compar- ing it to a longer, more expensive full examination with a pediatric ophthalmologist as the gold standard. The study finds that 30 c hildren have strabismus and 70 do not. How- ever, a fter undergoing the quick screening test, 60 children have abnormal results and 40 children have normal results. Table 1-1 shows the screening test result data. The screening test performance is described as follows: Sensitivity: The test correctly identifies 20 of every 30 children who have strabismus (67%). The equation is a/(a + c). The denominator, (a + c), represents all of the test subjects who have the disease (strabismus). Specificity: The test correctly identifies 30 of every 70 children who do not have strabismus (43%). The equation is d/(b + d). The denominator (b + d), represents all of the test subjects who do not have the disease (normal). Positive predictive value (PPV): If a child’s test results are abnormal, there is only a 1 in 3 chance (20/60) that the child actually has strabismus (33%). The equation is a/(a + b). The denominator, (a + b), represents all of the subjects with abnormal test results. Negative predictive value (NPV): If a child’s test results are normal, t here is a 3 in 4 chance (30/40) that the child is actually disease-free (75%). The equation is d/(d + c). The denominator, (d + c), represents all the test subjects with normal test results. Accuracy: The screening test is correct in 50 of 100 cases (50%). The equation to determine accuracy is (a + d)/(a + b +c + d). Table 1-1 Results for Strabismus Screening Test in Clinic Screening Test Result Strabismus No Strabismus Totals Abnormal a. Truly abnormal (20) b. Falsely abnormal (40) 60 Normal c. Falsely normal (10) d. Truly normal (30) 40 Totals 30 70 100 Sensitivity is 20/30 (67%); specificity is 30/70 (43%); positive predictive value is 20/60 (33%); negative predictive value is 30/40 (75%); accuracy is 50%. 16 Update on General Medicine Table 1-2 Results for Strabismus Screening Test in Shopping Center Screening Test Result Strabismus No Strabismus Totals Abnormal a. Truly abnormal (2) b. Falsely abnormal (58) 60 Normal c. Falsely normal (1) d. Truly normal (39) 40 Totals 3 97 100 Sensitivity is 2/3 (67%); specificity is 39/97 (40%); positive predictive value is 2/60 (3%); negative predictive value is 39/40 (98%). Sensitivity is the percentage of test subjects who both have the disease of interest and have abnormal test results, and specificity is the percentage of disease-free people who have normal results. However, it is also important to remember that neither sensitivity nor specificity takes into account the prevalence of disease in the study population. Table 1-2 illustrates the performance of the hypothetic al strabismus test if it yields the same results (60 children with abnormal test results and 40 children with normal test re- sults) when performed in a shopping center where the prevalence of strabismus is only 3% (much lower than in the situation previously discussed). The sensitivity is still 67%, and the specificity is about the same, at 40%. However, b ecause of the high number of falsely abnormal results, 58 c hildren without disease and only 2 c hildren who truly have strabis- mus would be referred for complete examinations. In this example, the PPV is only 3% (2/60). The NPV is 98% (39/40). Because of the low prevalence of strabismus in this set- ting, most children whose test results were abnormal would actually be disease-free. This increases the costs of unnecessary follow-up testing and increases anxiety for the parents. Clearly, the prevalence of disease in the population of interest and the screening test’s PPV and NPV should be considered before the test is used for screening a population. Choosing a gold standard is a key aspect of conducting a diagnostic testing study. The reader of such a study should ascertain whether the gold standard (in this case a pediatric ophthalmologist) was masked to the results of the strabismus test; if not, this may have created confirmatory bias, potentially artificially increasing the diagnostic precision of the screening test. The gold standard should also have been previously published and accepted by contemporaneous experts. Finally, the gold standard should be repeatable u nder the same conditions; for example, would the pediatric ophthalmologist come to the same diag- nosis (strabismus vs. no strabismus) if they examined the child a second time? In conclu- sion, the gold standard should be scrutinized for its applicability to the clinical situation. Complicating Features Using ROC curves to compare different screening thresholds with a continuous predictive variable When the screening test measures a continuous value, such as IOP, it becomes more com- plicated to evaluate the screening test. Figure 1-5 uses data from the Baltimore Eye Survey to graphically display sensitivity and specificity for each value of IOP. The usual cutoff for normal IOP, 21 mm Hg, has a sensitivity of 49% and a specificity of 90%. The intersection of sensitivity and specificity is the optimal threshold for maximum sensitivity and specific- ity in a screening test. This intersection occurs at 18 mm Hg, where the sensitivity is 65% Chapter 1: Using Research to Improve Clinical Practice 17 1 0.9 0.8 0.7 Sensitivity/Specificity 0.6 0.5 0.4 0.3 0.2 Sensitivity 0.1 Specificity 0 10 12 14 16 18 20 21 22 24 26 28 30 Intraocular Pressure (mm Hg) Figure 1-5 Sensitivity and specificity of an intraocular pressure (IOP) cutoff as a screening tool for glaucoma. For each IOP level (along the x-axis), the values for sensitivity and specificity are plotted. This demonstrates that with a higher level of IOP as a screening cutoff for glaucoma (for example, IOP >30 mm Hg), the sensitivity decreases and the specificity increases. (Used with permission from Tielsch JM, Katz J, Singh K, et al. A population-based evaluation of glaucoma screening: the Balti- more Eye Survey. Am J Epidemiol. 1991;134:1102–1110.) and the specificity is 66%. With continuous variables, like IOP, there is a trade-off between sensitivity and specificity: a higher sensitivity results in a lower specificity, and vice versa. Figure 1-6 depicts another graphical representation of sensitivity and specificity called a receiver operating characteristic (ROC) curve. By convention, an ROC curve plots sensitivity on the y-axis and (1 – specificity) on the x-axis. The larger the area under the curve, the more diagnostically precise is the screening test. The line with the diamond- shaped symbols represents a hypothetical screening test with optimal results; the line with the triangles represents a poor screening test with an ROC area of only 50%; and the line with the circles—the m iddle curve—represents the Baltimore Eye Survey data used in Figure 1-5. An ROC curve can inform selection of an optimal cutoff point for a screening test by identifying the sensitivity–specificity pair located closest to the upper left of the ROC plot. Overall, these figures demonstrate that IOP measurement is not a very good s creening tool for glaucoma because no cut-off reaches the ideal sensitivity/specificity (upper left of diamond line). Other significant factors in choosing a cutoff point for a screening test are the population to be screened and the relative importance of sensitivity and specificity. If the consequence of missing a diagnosis is very important such as blindness, an investiga- tor may choose a test with high sensitivity but poor specificity. For example, a low cutoff for erythrocyte sedimentation rate might be chosen for a person who has recent vision loss and who is suspected of having giant cell arteritis. Tielsch JM, Katz J, Singh K, et al. A population-based evaluation of glaucoma screening: the Baltimore Eye Survey. Am J Epidemiol. 1991;134(10):1102–1110. 18 Update on General Medicine 1 0.8 21 mm Hg 18 mm Hg 0.6 Sensitivity Hypothetical screening test that is optimal 0.4 Diagnostic precision of all possible IOP cutoffs 0.2 Hypothetical screening test that is useless 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 (1 – specificity) Figure 1-6 ROC curve of IOP as a screening tool for glaucoma with sensitivity on the y-axis and (1 − specificity) on the x-axis. The middle line replots the data from Figure 1-5, showing all combinations of IOP. Two boxes identify the diagnostic precision of IOP ≥18 mm Hg and IOP ≥21 mm Hg. The other lines represent an optimal (upper line) and a useless (lower line) screen- ing test, respectively. (Produced with data from Tielsch JM, Katz J, Singh K, et al. A population-based evaluation of glaucoma screening: the Baltimore Eye Survey. Am J Epidemiol. 1991;134:1102–1110.) Using ROC curves to compare different screening devices Studies can use ROC curves to compare new diagnostic tests. ROC curves can be used to compare tests that use different units or different scales. Figure 1-7 shows 3 ROC curves illustrating the ability of 3 glaucoma imaging devices to discriminate between healthy eyes and eyes with glaucomatous visual field loss via imaging of the optic nerve head and nerve fiber layer. The area under each ROC curve represents a summary measure of the relative efficacy of the screening test. The ROC curves appear similar for inferior average nerve fiber layer thickness as measured with OCT and for scanning l aser polarimetry with variable corneal compensation (GDx VCC nerve fiber index), while the ROC curve for confocal scanning laser ophthalmoscopy (HRT linear discriminant function) is lower. In other words, the figure suggests a higher diagnostic precision for scanning laser polarim- etry and OCT than confocal scanning laser ophthalmoscopy. Medeiros FA, Zangwill LM, Bowd C, Weinreb RN. Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and Stratus OCT optical coherence tomograph for the detection of glaucoma. Arch Ophthalmol. 2004;122(6):827–837. The effect of pretest probability of disease Pretest probability of disease uses knowledge of the patient before any screening or diag- nostic tests are performed. For example, the investigator may know that the patient has a first-degree relative with glaucoma as well as a thinner-than-average central corneal thick- ness (both are risk factors for glaucoma). This information suggests a pretest probability Chapter 1: Using Research to Improve Clinical Practice 19 1 0.9 0.8 Sensitivity 0.7 0.6 GDx VCC nerve fiber index 0.5 HRT linear discriminant function OCT inferior average NFL thickness 0.4 0.3 0 0.2 0.4 0.6 0.8 1.0 1 – specificity Figure 1-7 ROC curve of 3 glaucoma imaging devices. The single parameter chosen for dis- play for each instrument was the one that performed the best in the authors’ study. There was no statistically significant difference in the area under the ROC curves for these 3 para meters. (The HRT linear discriminant function is from a paper by Bathija et al, referenced by Medeiros et al; the GDx and OCT parameters are standard test outputs provided by the manufacturers. Graph drawn with data from Medeiros FA, Zangwill LM, Bowd C, Weinreb RN. Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and Stratus OCT optical coherence tomograph for the detection of glaucoma. Arch Ophthalmol. 2004;122:827–837.) of glaucoma about 3 times higher than that of a person picked at random from the general population. How much does a diagnostic test improve the ability to diagnose glaucoma in this patient with a higher pretest probability? How much higher is the relative risk of glaucoma if the test result is positive? Bayes theorem allows the pretest probability of disease to be combined with the diag- nostic precision of a screening test to produce a posttest probability of disease. To use this theorem, the likelihood ratio must be calculated. The likelihood ratio of a positive test is the sensitivity divided by (1 − specificity). For a sample test with 80% sensitivity and 90% specificity (0.8/[1 − 0.9]), the positive likelihood ratio is 8. The likelihood ratio of a nega- tive test is (1 − sensitivity) divided by the specificity. For the same sample test, the negative likelihood ratio is (1 − 0.8)/0.9, or 0.22. Positive likelihood ratios start at 1 and continue to infinity—the bigger, the better. Ne

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