Clinical epidemiology: the essentials
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia ; Baltimore ; New York
Wolters Kluwer
[2021]
|
| Ausgabe: | Sixth edition, international edition |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | xiv, 274 Seiten Illustrationen |
| ISBN: | 9781975140984 1975140982 |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents Incidence Studies 21 Cumulative Incidence 21 Incidence Density (Person-Years) 21 Basic Elements of Frequency Studies Clinical Questions and Clinical Epidemiology Health Outcomes 2 The Scientific Basis for Clinical Medicine Basic Principles Variables 3 6 6 Populations and Samples 6 Bias (Systematic Error) Distribution of Disease by Time, Place, and Person 25 6 The Effects of Bias and Chance Are Cumulative 10 Internal and External Validity Organization of This Book Prevalence Incidence Time 25 Place 26 Person 26 Uses of Prevalence Studies 11 17 3 Abnormality Types of Data 18 32 Nominal Data 18 18 Prevalence and Incidence in Relation to Time 19 32 Interval Data 32 Performance of Measurements Validity Some Other Rates Range 20 21 32 Ordinal Data Relationships Among Prevalence, Incidence, and Duration of Disease 19 Prevalence Studies 27 What Are Prevalence Studies Not Particularly Good for? 28 12 Studies of Prevalence and Incidence 27 What Are Prevalence Studies Good for? 12 Are Words Suitable Substitutes for Numbers? Prevalence and Incidence What Is a Case? Defining the Numerator 22 Does the Study Sample Represent the Population? 25 10 Information and Decisions 22 What Is the Population? Defining the Denominator 24 5 Numbers and Probability Chance 2 20 33 Reliability 34 35 Responsiveness Interpretability 35 35 33 31
x Contents Variation 36 Likelihood Ratios Variation Resulting from Measurement Òdds 36 68 68 Variation Resulting from Biologic Differences 36 Definitions Total Variation Why Use Likelihood Ratios? 37 Effects of Variation Distributions 69 Use of Likelihood Ratios 38 Multiple Tests Describing Distributions 39 Abnormal = Unusual 39 Serial Testing 41 42 74 74 Assumption of Independence 74 43 45 Abnormal = Treating the Condition Leads to a Better Clinical Outcome 47 Regression to the Mean 5 48 Risk: Basic Principles 78 Risk Measurement Risk Factors 4 73 Serial Likelihood Ratios Abnormal = Biologic Dysfunction Abnormal = Illness 72 Clinical Prediction Rules The Normal Distribution 70 71 Parallel Testing 39 Criteria for Abnormality 69 Calculating Likelihood Ratios 39 Actual Distributions 69 79 79 Recognizing Risk Factors Diagnosis 53 Long Latency 80 80 Immediate Versus Distant Causes Simplifying Data 53 Common Exposure to Risk Factors The Accuracy of a Test Result The Gold Standard 54 Low Incidence of Disease 55 Small Risk Sensitivity and Specificity Definitions 55 81 Use of Specific Tests Risk Prediction Models 57 The Receiver Operator Characteristic (ROC) Curve Studies of Diagnostic Tests Combining Multiple Factors Discrimination Calibration 58 60 61 82 83 83 85 Validating Models 59 86 External Validation 86 Comparing Models 87 Assessing Models in Clinical Practice 61 Risk Stratification Imperfect Gold Standards Definitions 62 87 87 Clinical Uses of Risk Factors, Prognostic Factors, and Risk Prediction Tools 88 64 64 Determinants of Predictive Value 81 82 Evaluating Risk
Prediction Tools Spectrum of Patients—the Study Population Predictive Value 81 Risk Factors May or May Not Be Causal 55 Trade-Offs Between Sensitivity and Specificity 57 Chance 80 81 Multiple Causes and Multiple Effects 55 Use of Sensitive Tests Bias 80 Risk Prediction and Pretest Probability for Diagnostic Testing 88 65 Estimating Prevalence (Pretest Probability) Implications for Interpreting the Medical Literature 68 66 Using Risk Factors to Choose Treatment 89 Risk Stratification for Screening Programs 89 Removing Risk Factors to Prevent Disease 89
Contents Selecting Controls 6 Risk: Exposure to Disease 92 Studies of Risk Odds Ratio Calculation When Experiments Are Not Possible or Ethical Cohorts 92 93 93 Prospective and Historical Cohort Studies 94 Relative Risk 98 99 100 Extraneous Variables 101 Differences in Risk and Prognostic Factors 126 101 Simple Descriptions of Risk 101 The Patients Are Different 102 Working Definition Randomization The Rates Are Different 102 Confirming Confounding Control of Confounding 102 103 Elements of Prognostic Studies Patient Sample 104 104 105 Overall Strategy for Control of Confounding 106 106 Mendelian Randomization Zero Time 128 Follow-Up 129 106 Describing Prognosis Risk: From Disease to Exposure 111 Case-Control Studies Design of Case-Control Studies Selecting Cases 114 114 114 130 132 Interpreting Survival Curves 133 Identifying Prognostic Factors 133 Case Series 134 Clinical Prediction Rules 112 The Source Population 130 Survival of a Cohort Survival Curves 7 129 129 A Trade-Off: Simplicity Versus More Information 129 Survival Analysis 107 127 127 Outcomes of Disease 105 Observational Studies and Cause Effect Modification 127 Clinical Course and Natural History of Disease 127 103 Multivariable Adjustment 127 127 The Factors May be Different 103 Standardization 127 The Outcomes Are Different 102 Potential Confounders Stratification 121 99 Taking Other Variables into Account Restriction 120 99 Interpreting Attributable and Relative Risk Matching Investigation of a Disease Outbreak 99 Population Risk Confounding Odds Ratio as a Direct Estimate of Relative Risk 120 Extraneous
Variables Ways to Express and Compare Risk Attributable Risk 119 Odds Ratio as an Indirect Estimate of Relative Risk 119 Controlling for Advantages and Disadvantages of Cohort Studies 96 Absolute Risk 116 The Odds Ratio: An Estimate of Relative Risk 118 92 Cohort Studies 114 Measuring Exposure Bias in Cohort Studies Sampling Bias 136 Migration Bias 136 134 135 ХІ
xii Contents Measurement Bias 136 Bias from Non-differential M ^classification 137 Bias from Missing Data 137 Bias, Perhaps, But Does It Matter? Sensitivity Analysis Preventive Activities in Clinical Settings 162 137 137 Types of Clinical Prevention Levels of Prevention Primary Prevention 163 Secondary Prevention Tertiary Prevention Ideas and Evidence Ideas 142 144 Burden of Suffering Observational and Experimental Studies of Treatment Effects 144 Randomized Controlled Trials Ethics 166 Treatment in Secondary Prevention Intervention Treatment in Tertiary Prevention 147 Comparison Groups Prevalence and Incidence Screens 148 Differences Arising After Randomization 149 150 Assessment of Outcomes Efficacy and Effectiveness 152 172 172 Detection and Incidence Methods for Calculating Sensitivity 173 Variations on Basic Randomized Trials 155 Tailoring the Results of Trials to Individual Patients 156 156 Effectiveness in Individual Patients 156 156 Alternatives to Randomized Controlled Trials 157 Limitations of Randomized Trials Observational Studies of Interventions 157 Phases of Clinical Trials 169 169 High Sensitivity and Specificity Superiority, Equivalence, and Noninferiority 157 153 Low Positive Predictive Value Simplicity and Low Cost Safety 174 174 175 Acceptable to Patients and Clinicians 175 Unintended Consequences of Screening 175 Risk of False-Positive Result 176 Risk of Negative Labeling Effect 176 Risk of Overdiagnosis (Pseudodisease) in Cancer Screening 177 Incidentalomas 158 Randomized Versus Observational Studies? Special Biases Performance of Screening Tests 150
Intention-to-Treat and Explanatory Trials 153 Clinical Databases 167 168 Methodologie Issues in Evaluating Screening Programs 169 147 Allocating Treatment N of 1 Trials 166 Treatment in Primary Prevention 145 Subgroups 165 Effectiveness of Treatment 144 145 Blinding 164 Scientific Approach to Clinical Prevention 165 143 Studies of Treatment Effects Sampling 164 Confusion About Primary, Secondary, and Tertiary Prevention 164 142 Testing Ideas 163 163 178 Changes in Screening Tests and Treatments Over Time 179 158 158 Weighing Benefits Against Harms of Prevention 179
xiii Contents Reversible Associations Consistency Biologic Plausibility Two Approaches to Chance Hypothesis Testing Specificity 185 Analogy 186 False-Positive and False-Negative Statistical Results 186 Concluding That a Treatment Works Dichotomous and Exact P Values Concluding That a Treatment Does Not Work 189 How Many Study Patients Are Enough? 190 190 Point Estimates and Confidence Intervals Detecting Rare Events 194 Multiple Comparisons 194 Bayesian Reasoning Summarizing the Evidence 219 Traditional Reviews 219 Systematic Reviews 220 190 193 Selecting Studies 220 221 Assessing Study Quality and Characteristics 223 225 226 Are the Studies Similar Enough to Justify Combining? 226 How Are the Results Pooled? 227 Identifying Reasons for Heterogeneity 197 Additional Meta-Analysis Methods 198 Multivariable Methods 216 Combining Studies in Meta-Analyses 196 Noninferiority Studies 214 Summarizing Results Statistical Power After a Study Is Completed 194 Multiple Outcomes 212 Defining a Specific Question Estimating Sample Size Requirements Subgroup Analysis Modeling 13 188 Statistical Power 212 Aggregate Risk Studies 187 Statistical Significance and Clinical Importance 187 Statistical Tests 211 212 Weighing the Evidence 186 211 211 Patient-Level Meta-Analysis 198 Network Meta-Analysis 200 228 229 229 230 Cumulative Meta-Analyses 230 Systematic Reviews of Observational and Diagnostic Studies 231 Strengths and Weaknesses of Meta-Analyses Basic Principles 232 205 Single Causes Multiple Causes 14 205 205 Proximity of Cause to Effect Indirect Evidence for Cause 206 Basic Principles
208 Examining Individual Studies 208 Hierarchy of Research Designs 209 209 Does Cause Precede Effect? 210 Strength of the Association 210 Dose-Response Relationships 210 236 236 Do It Yourself or Delegate? Which Medium? 236 237 Grading Information The Body of Evidence for and Against Cause Knowledge Management 237 Misleading Reports of Research Findings 237 Looking Up Answers to Clinical Questions 239 Solutions 239 Surveillance on New Developments 241
XIV Journals Contents 242 Reading Journals 243 APPENDIX A: ANSWERS TO REVIEW QUESTIONS 249 Guiding Patients Quest for Health Information 245 APPENDIX B: ADDITIONAL READINGS Putting Knowledge Management into Practice 245 INDEX 265 0 262
Clinical Epidemiologií л, . Wåmt The Essentials Sixth Edition Grant S. Fletcher, MD, MPH Gain the confidence and clinical judgment to form the most effective conclusions in patient care! Written by expert educators and updated to reflect the latest clinical approaches, Clinical Epidemiology: The Essentials familiarizes you with the principles of evidence-based medicine and guides you in developing and applying methods of clinical observation essential to successful clinical outcomes. ■ Updated content throughout equips you with the most current practices in clinical epidemiology. ■ Clinical emphasis helps you confidently evaluate the effectiveness of guidelines and integrate them into practice. ■ Updated vignette-style end-of-chapter questions place concepts in a clinical context to reinforce your understanding. ■ Key Word lists at the start of each chapter acquaint you with critical terminology for clinical success. ■ Example boxes clarify the clinical implications of important concepts with relevant real-world patient care scenarios. ■ Appendix of Additional Readings highlights trusted resources for further review.
|
| adam_txt |
Contents Incidence Studies 21 Cumulative Incidence 21 Incidence Density (Person-Years) 21 Basic Elements of Frequency Studies Clinical Questions and Clinical Epidemiology Health Outcomes 2 The Scientific Basis for Clinical Medicine Basic Principles Variables 3 6 6 Populations and Samples 6 Bias (Systematic Error) Distribution of Disease by Time, Place, and Person 25 6 The Effects of Bias and Chance Are Cumulative 10 Internal and External Validity Organization of This Book Prevalence Incidence Time 25 Place 26 Person 26 Uses of Prevalence Studies 11 17 3 Abnormality Types of Data 18 32 Nominal Data 18 18 Prevalence and Incidence in Relation to Time 19 32 Interval Data 32 Performance of Measurements Validity Some Other Rates Range 20 21 32 Ordinal Data Relationships Among Prevalence, Incidence, and Duration of Disease 19 Prevalence Studies 27 What Are Prevalence Studies Not Particularly Good for? 28 12 Studies of Prevalence and Incidence 27 What Are Prevalence Studies Good for? 12 Are Words Suitable Substitutes for Numbers? Prevalence and Incidence What Is a Case? Defining the Numerator 22 Does the Study Sample Represent the Population? 25 10 Information and Decisions 22 What Is the Population? Defining the Denominator 24 5 Numbers and Probability Chance 2 20 33 Reliability 34 35 Responsiveness Interpretability 35 35 33 31
x Contents Variation 36 Likelihood Ratios Variation Resulting from Measurement Òdds 36 68 68 Variation Resulting from Biologic Differences 36 Definitions Total Variation Why Use Likelihood Ratios? 37 Effects of Variation Distributions 69 Use of Likelihood Ratios 38 Multiple Tests Describing Distributions 39 Abnormal = Unusual 39 Serial Testing 41 42 74 74 Assumption of Independence 74 43 45 Abnormal = Treating the Condition Leads to a Better Clinical Outcome 47 Regression to the Mean 5 48 Risk: Basic Principles 78 Risk Measurement Risk Factors 4 73 Serial Likelihood Ratios Abnormal = Biologic Dysfunction Abnormal = Illness 72 Clinical Prediction Rules The Normal Distribution 70 71 Parallel Testing 39 Criteria for Abnormality 69 Calculating Likelihood Ratios 39 Actual Distributions 69 79 79 Recognizing Risk Factors Diagnosis 53 Long Latency 80 80 Immediate Versus Distant Causes Simplifying Data 53 Common Exposure to Risk Factors The Accuracy of a Test Result The Gold Standard 54 Low Incidence of Disease 55 Small Risk Sensitivity and Specificity Definitions 55 81 Use of Specific Tests Risk Prediction Models 57 The Receiver Operator Characteristic (ROC) Curve Studies of Diagnostic Tests Combining Multiple Factors Discrimination Calibration 58 60 61 82 83 83 85 Validating Models 59 86 External Validation 86 Comparing Models 87 Assessing Models in Clinical Practice 61 Risk Stratification Imperfect Gold Standards Definitions 62 87 87 Clinical Uses of Risk Factors, Prognostic Factors, and Risk Prediction Tools 88 64 64 Determinants of Predictive Value 81 82 Evaluating Risk
Prediction Tools Spectrum of Patients—the Study Population Predictive Value 81 Risk Factors May or May Not Be Causal 55 Trade-Offs Between Sensitivity and Specificity 57 Chance 80 81 Multiple Causes and Multiple Effects 55 Use of Sensitive Tests Bias 80 Risk Prediction and Pretest Probability for Diagnostic Testing 88 65 Estimating Prevalence (Pretest Probability) Implications for Interpreting the Medical Literature 68 66 Using Risk Factors to Choose Treatment 89 Risk Stratification for Screening Programs 89 Removing Risk Factors to Prevent Disease 89
Contents Selecting Controls 6 Risk: Exposure to Disease 92 Studies of Risk Odds Ratio Calculation When Experiments Are Not Possible or Ethical Cohorts 92 93 93 Prospective and Historical Cohort Studies 94 Relative Risk 98 99 100 Extraneous Variables 101 Differences in Risk and Prognostic Factors 126 101 Simple Descriptions of Risk 101 The Patients Are Different 102 Working Definition Randomization The Rates Are Different 102 Confirming Confounding Control of Confounding 102 103 Elements of Prognostic Studies Patient Sample 104 104 105 Overall Strategy for Control of Confounding 106 106 Mendelian Randomization Zero Time 128 Follow-Up 129 106 Describing Prognosis Risk: From Disease to Exposure 111 Case-Control Studies Design of Case-Control Studies Selecting Cases 114 114 114 130 132 Interpreting Survival Curves 133 Identifying Prognostic Factors 133 Case Series 134 Clinical Prediction Rules 112 The Source Population 130 Survival of a Cohort Survival Curves 7 129 129 A Trade-Off: Simplicity Versus More Information 129 Survival Analysis 107 127 127 Outcomes of Disease 105 Observational Studies and Cause Effect Modification 127 Clinical Course and Natural History of Disease 127 103 Multivariable Adjustment 127 127 The Factors May be Different 103 Standardization 127 The Outcomes Are Different 102 Potential Confounders Stratification 121 99 Taking Other Variables into Account Restriction 120 99 Interpreting Attributable and Relative Risk Matching Investigation of a Disease Outbreak 99 Population Risk Confounding Odds Ratio as a Direct Estimate of Relative Risk 120 Extraneous
Variables Ways to Express and Compare Risk Attributable Risk 119 Odds Ratio as an Indirect Estimate of Relative Risk 119 Controlling for Advantages and Disadvantages of Cohort Studies 96 Absolute Risk 116 The Odds Ratio: An Estimate of Relative Risk 118 92 Cohort Studies 114 Measuring Exposure Bias in Cohort Studies Sampling Bias 136 Migration Bias 136 134 135 ХІ
xii Contents Measurement Bias 136 Bias from "Non-differential" M ^classification 137 Bias from Missing Data 137 Bias, Perhaps, But Does It Matter? Sensitivity Analysis Preventive Activities in Clinical Settings 162 137 137 Types of Clinical Prevention Levels of Prevention Primary Prevention 163 Secondary Prevention Tertiary Prevention Ideas and Evidence Ideas 142 144 Burden of Suffering Observational and Experimental Studies of Treatment Effects 144 Randomized Controlled Trials Ethics 166 Treatment in Secondary Prevention Intervention Treatment in Tertiary Prevention 147 Comparison Groups Prevalence and Incidence Screens 148 Differences Arising After Randomization 149 150 Assessment of Outcomes Efficacy and Effectiveness 152 172 172 Detection and Incidence Methods for Calculating Sensitivity 173 Variations on Basic Randomized Trials 155 Tailoring the Results of Trials to Individual Patients 156 156 Effectiveness in Individual Patients 156 156 Alternatives to Randomized Controlled Trials 157 Limitations of Randomized Trials Observational Studies of Interventions 157 Phases of Clinical Trials 169 169 High Sensitivity and Specificity Superiority, Equivalence, and Noninferiority 157 153 Low Positive Predictive Value Simplicity and Low Cost Safety 174 174 175 Acceptable to Patients and Clinicians 175 Unintended Consequences of Screening 175 Risk of False-Positive Result 176 Risk of Negative Labeling Effect 176 Risk of Overdiagnosis (Pseudodisease) in Cancer Screening 177 Incidentalomas 158 Randomized Versus Observational Studies? Special Biases Performance of Screening Tests 150
Intention-to-Treat and Explanatory Trials 153 Clinical Databases 167 168 Methodologie Issues in Evaluating Screening Programs 169 147 Allocating Treatment N of 1 Trials 166 Treatment in Primary Prevention 145 Subgroups 165 Effectiveness of Treatment 144 145 Blinding 164 Scientific Approach to Clinical Prevention 165 143 Studies of Treatment Effects Sampling 164 Confusion About Primary, Secondary, and Tertiary Prevention 164 142 Testing Ideas 163 163 178 Changes in Screening Tests and Treatments Over Time 179 158 158 Weighing Benefits Against Harms of Prevention 179
xiii Contents Reversible Associations Consistency Biologic Plausibility Two Approaches to Chance Hypothesis Testing Specificity 185 Analogy 186 False-Positive and False-Negative Statistical Results 186 Concluding That a Treatment Works Dichotomous and Exact P Values Concluding That a Treatment Does Not Work 189 How Many Study Patients Are Enough? 190 190 Point Estimates and Confidence Intervals Detecting Rare Events 194 Multiple Comparisons 194 Bayesian Reasoning Summarizing the Evidence 219 Traditional Reviews 219 Systematic Reviews 220 190 193 Selecting Studies 220 221 Assessing Study Quality and Characteristics 223 225 226 Are the Studies Similar Enough to Justify Combining? 226 How Are the Results Pooled? 227 Identifying Reasons for Heterogeneity 197 Additional Meta-Analysis Methods 198 Multivariable Methods 216 Combining Studies in Meta-Analyses 196 Noninferiority Studies 214 Summarizing Results Statistical Power After a Study Is Completed 194 Multiple Outcomes 212 Defining a Specific Question Estimating Sample Size Requirements Subgroup Analysis Modeling 13 188 Statistical Power 212 Aggregate Risk Studies 187 Statistical Significance and Clinical Importance 187 Statistical Tests 211 212 Weighing the Evidence 186 211 211 Patient-Level Meta-Analysis 198 Network Meta-Analysis 200 228 229 229 230 Cumulative Meta-Analyses 230 Systematic Reviews of Observational and Diagnostic Studies 231 Strengths and Weaknesses of Meta-Analyses Basic Principles 232 205 Single Causes Multiple Causes 14 205 205 Proximity of Cause to Effect Indirect Evidence for Cause 206 Basic Principles
208 Examining Individual Studies 208 Hierarchy of Research Designs 209 209 Does Cause Precede Effect? 210 Strength of the Association 210 Dose-Response Relationships 210 236 236 Do It Yourself or Delegate? Which Medium? 236 237 Grading Information The Body of Evidence for and Against Cause Knowledge Management 237 Misleading Reports of Research Findings 237 Looking Up Answers to Clinical Questions 239 Solutions 239 Surveillance on New Developments 241
XIV Journals Contents 242 "Reading" Journals 243 APPENDIX A: ANSWERS TO REVIEW QUESTIONS 249 Guiding Patients'Quest for Health Information 245 APPENDIX B: ADDITIONAL READINGS Putting Knowledge Management into Practice 245 INDEX 265 0 262
Clinical Epidemiologií л, . Wåmt The Essentials Sixth Edition Grant S. Fletcher, MD, MPH Gain the confidence and clinical judgment to form the most effective conclusions in patient care! Written by expert educators and updated to reflect the latest clinical approaches, Clinical Epidemiology: The Essentials familiarizes you with the principles of evidence-based medicine and guides you in developing and applying methods of clinical observation essential to successful clinical outcomes. ■ Updated content throughout equips you with the most current practices in clinical epidemiology. ■ Clinical emphasis helps you confidently evaluate the effectiveness of guidelines and integrate them into practice. ■ Updated vignette-style end-of-chapter questions place concepts in a clinical context to reinforce your understanding. ■ Key Word lists at the start of each chapter acquaint you with critical terminology for clinical success. ■ Example boxes clarify the clinical implications of important concepts with relevant real-world patient care scenarios. ■ Appendix of Additional Readings highlights trusted resources for further review. |
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| publisher | Wolters Kluwer |
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| spelling | Fletcher, Grant S. Verfasser (DE-588)106382463X aut Clinical epidemiology the essentials Grant S. Fletcher, MD, MPH, Associate Professor of Medicine, The University of Washington School of Medicine Sixth edition, international edition Philadelphia ; Baltimore ; New York Wolters Kluwer [2021] xiv, 274 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Epidemiologic Methods Epidemiologie (DE-588)4015016-1 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Epidemiologie (DE-588)4015016-1 s DE-604 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032048302&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032048302&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Fletcher, Grant S. Clinical epidemiology the essentials Epidemiologic Methods Epidemiologie (DE-588)4015016-1 gnd |
| subject_GND | (DE-588)4015016-1 (DE-588)4123623-3 |
| title | Clinical epidemiology the essentials |
| title_auth | Clinical epidemiology the essentials |
| title_exact_search | Clinical epidemiology the essentials |
| title_exact_search_txtP | Clinical epidemiology the essentials |
| title_full | Clinical epidemiology the essentials Grant S. Fletcher, MD, MPH, Associate Professor of Medicine, The University of Washington School of Medicine |
| title_fullStr | Clinical epidemiology the essentials Grant S. Fletcher, MD, MPH, Associate Professor of Medicine, The University of Washington School of Medicine |
| title_full_unstemmed | Clinical epidemiology the essentials Grant S. Fletcher, MD, MPH, Associate Professor of Medicine, The University of Washington School of Medicine |
| title_short | Clinical epidemiology |
| title_sort | clinical epidemiology the essentials |
| title_sub | the essentials |
| topic | Epidemiologic Methods Epidemiologie (DE-588)4015016-1 gnd |
| topic_facet | Epidemiologic Methods Epidemiologie Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032048302&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032048302&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT fletchergrants clinicalepidemiologytheessentials |