Translational Cardiology provides a cardiology-specific instructional guide to translational medical research that will serve as a practical, step-by-step roadmap for taking a biomedical device, potential therapeutic agent, or research question from idea through demonstrated clinical benefit. Fundamentally, the volume aims to help bridge the gap between current research and practice. Written by a team of expert medical, biomedical engineering, and clinical research experts in cardiology, this book provides a clear process for understanding, designing, executing, and analyzing clinical and translational research.…mehr
Translational Cardiology provides a cardiology-specific instructional guide to translational medical research that will serve as a practical, step-by-step roadmap for taking a biomedical device, potential therapeutic agent, or research question from idea through demonstrated clinical benefit. Fundamentally, the volume aims to help bridge the gap between current research and practice. Written by a team of expert medical, biomedical engineering, and clinical research experts in cardiology, this book provides a clear process for understanding, designing, executing, and analyzing clinical and translational research.
1. Defining the problem to solve 2. Types of problems 3. Drug discovery 4. Device discovery 5. Device classification 6. Other product types 7. Drug safety 8. Device prototyping 9. Device testing 10. Introduction to clinical research: What is it? Why is it needed? 11. The question: Types of research questions and how to develop them 12. Study population: Who and why them? 13. Outcome measurements: What data is being collected and why? 14. Presenting data 15. Common issues in analysis 16. Basic statistical principles 17. Distributions 18. Hypotheses and error types 19. Power 20. Regression 21. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank 22. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel 23. Analysis of variance 24. Correlation 25. Biases 26. Basic science statistics 27. Sample forms and templates 28. Design principles: Hierarchy of study types 29. Case series: Design, measures, classic example 30. Case-control study: Design, measures, classic example 31. Cohort study: Design, measures, classic example 32. Cross-section study: Design, measures, classic example 33. Clinical trials: Design, measures, classic example 34. Meta-analysis: Design, measures, classic example 35. Cost-effectiveness study: Design, measures, classic example 36. Diagnostic test evaluation: Design, measures, classic example 37. Reliability study: Design, measures, classic example 38. Database studies: Design, measures, classic example 39. Surveys and questionnaires: Design, measures, classic example 40. Qualitative methods and mixed methods 41. Randomized control: Design, measures, classic example 42. Nonrandomized control: Design, measures, classic example 43. Historical control: Design, measures, classic example 44. Cross-over: Design, measures, classic example 45. Withdrawal studies: Design, measures, classic example 46. Factorial design: Design, measures, classic example 47. Group allocation: Design, measures, classic example 48. Hybrid design: Design, measures, classic example 49. Large, pragmatic: Design, measures, classic example 50. Equivalence and noninferiority: Design, measures, classic example 51. Adaptive: Design, measures, classic example 52. Randomization: Fixed or adaptive procedures 53. Blinding: Who and how? 54. Multicenter considerations Registries 55. IDEAL Framework 56. Optimizing the question: Balancing significance and feasibility 57. Meaningful outcome measurements 58. Sample size 59. Budgeting 60. Ethics and review boards 61. Regulatory considerations for new drugs and devices 62. Funding approaches 63. Subject recruitment 64. Data management 65. Quality control 66. Report forms: Harm and Quality of Life 67. Subject adherence 68. Survival analysis 69. Monitoring committee in clinical trials 70. FDA overview 71. New drug application 72. Device pathways 73. Non-US regulatory 74. Post-Market Drug Safety Monitoring 75. Post-Market Device Safety Monitoring 76. Patent basics 77. Venture pathways
1. Defining the problem to solve 2. Types of problems 3. Drug discovery 4. Device discovery 5. Device classification 6. Other product types 7. Drug safety 8. Device prototyping 9. Device testing 10. Introduction to clinical research: What is it? Why is it needed? 11. The question: Types of research questions and how to develop them 12. Study population: Who and why them? 13. Outcome measurements: What data is being collected and why? 14. Presenting data 15. Common issues in analysis 16. Basic statistical principles 17. Distributions 18. Hypotheses and error types 19. Power 20. Regression 21. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank 22. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel 23. Analysis of variance 24. Correlation 25. Biases 26. Basic science statistics 27. Sample forms and templates 28. Design principles: Hierarchy of study types 29. Case series: Design, measures, classic example 30. Case-control study: Design, measures, classic example 31. Cohort study: Design, measures, classic example 32. Cross-section study: Design, measures, classic example 33. Clinical trials: Design, measures, classic example 34. Meta-analysis: Design, measures, classic example 35. Cost-effectiveness study: Design, measures, classic example 36. Diagnostic test evaluation: Design, measures, classic example 37. Reliability study: Design, measures, classic example 38. Database studies: Design, measures, classic example 39. Surveys and questionnaires: Design, measures, classic example 40. Qualitative methods and mixed methods 41. Randomized control: Design, measures, classic example 42. Nonrandomized control: Design, measures, classic example 43. Historical control: Design, measures, classic example 44. Cross-over: Design, measures, classic example 45. Withdrawal studies: Design, measures, classic example 46. Factorial design: Design, measures, classic example 47. Group allocation: Design, measures, classic example 48. Hybrid design: Design, measures, classic example 49. Large, pragmatic: Design, measures, classic example 50. Equivalence and noninferiority: Design, measures, classic example 51. Adaptive: Design, measures, classic example 52. Randomization: Fixed or adaptive procedures 53. Blinding: Who and how? 54. Multicenter considerations Registries 55. IDEAL Framework 56. Optimizing the question: Balancing significance and feasibility 57. Meaningful outcome measurements 58. Sample size 59. Budgeting 60. Ethics and review boards 61. Regulatory considerations for new drugs and devices 62. Funding approaches 63. Subject recruitment 64. Data management 65. Quality control 66. Report forms: Harm and Quality of Life 67. Subject adherence 68. Survival analysis 69. Monitoring committee in clinical trials 70. FDA overview 71. New drug application 72. Device pathways 73. Non-US regulatory 74. Post-Market Drug Safety Monitoring 75. Post-Market Device Safety Monitoring 76. Patent basics 77. Venture pathways
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