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MARIEL LOPEZ & MARITZA RENEAU Foreign Languages

MARIEL LOPEZ & MARITZA RENEAU Foreign Languages. Warm-Up. Identification and Classification of Outcome Medical condition Psychological or social problem Positive Identification of Exposure Higher probability Protective effect. Warm-up. Outcome.

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MARIEL LOPEZ & MARITZA RENEAU Foreign Languages

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  1. MARIEL LOPEZ & MARITZA RENEAU Foreign Languages

  2. Warm-Up • Identification and Classification of Outcome • Medical condition • Psychological or social problem • Positive • Identification of Exposure • Higher probability • Protective effect

  3. Warm-up Outcome Risk Factor-Possible effect

  4. Warm-up Outcome Risk Factor-Possible effect

  5. Warm-up • Enduring Epidemiological Understanding: Making group comparison and identifying association • General model • Specific model : Smoking and lung cancer

  6. Warm-up Association of interest Exposure Disease

  7. Warm-up Association of interest Smoking Lung cancer • What do you think is the best method to demonstrate a causal relation? Choose the best answer • Experimental study • Observational study.

  8. Warm-up Association of interest Smoking Lung cancer • What do you think is the best method to demonstrate a causal relation? Choose the best answer • Observational study. Choose the best answer • Case-control • Cohort • Cross-sectional

  9. Warm-up • Cohort study- handout • Design • Advantages and disadvantages

  10. Warm-up Association of interest Smoking Lung cancer • Can you think of some examples of other exposures or lifestyle choices that might be the real culprits in causing lung cancer?

  11. Enduring Epidemiological Understanding • Explaining Association and Judging Causation

  12. LESSON OBJECTIVES • To Understand Confounding • To Calculate and Interpret Relative Risk • To use Stratification in order to Identify Confounding Variables • In what phase of the study can stratification be used? • Design • Analysis

  13. Introduction- Confounding VariableBedsores and Mortality Association of interest Mortality Bedsores Medical Severity CV • Can you think of some examples of other exposures or lifestyle choices that might be the real culprits in causing Mortality?

  14. Bedsores and Mortality Study • Objective: The association between bedsores and death among elderly hip fracture patients. • Sample: 9,400 patients aged 60 and over, admitted with hip fracture to one of 20 study hospitals. • Methods: Medical charts were reviewed by research nurses in order to identify exposure and outcome.

  15. Analysis – Bedsores and MortalityRR- Unadjusted

  16. Analysis – Bedsores and MortalityRR- Unadjusted RR=.096/.033=2.9

  17. Introduction- Confounding VariableBedsores and Mortality Association of interest Mortality Bedsores Medical Severity CV • Can you think of some examples of other exposures or lifestyle choices that might be the real culprits in causing Mortality?

  18. Analysis – Bedsores and MortalityAdjusted by Medical Severity (PCV) RR U=.096/.033=2.9 High Medical Severity Group – 5 or more diseases when admitted to hospital RR=55/106= 1.04 5/10 Low Medical Severity Group- <5 RR=24/718= 1.02 281/8,566

  19. Bedsores and MortalityPCV Medical Severity • Is Medical Severity a confounding variable? • According to the stratification analysis…. • According to the definition • CV Outcome • We would expect that the people with HMS would have a higher probability of death that people with LMS • CV RF • We would expect that people with HMS would have a higher probability of bedsores that people with LMS.

  20. Analysis – Bedsores and MortalityAdjusted by Medical Severity (PCV) MS Mortality High Medical Severity Group – 5 or more diseases when admitted to hospital Proportion of HMS who died= 60/116= 51.7% Low Medical Severity Group- <5 Proportion of HMS who died= 305/9,284= 3.3%

  21. Analysis – Bedsores and MortalityAdjusted by Medical Severity (PCV) MS Bedsores High Medical Severity Group – 5 or more diseases when admitted to hospital Proportion of people with bedsores among those with HMS 106/116= 91.4% Low Medical Severity Group- <5 Proportion of people with bedsores among those with LMS 718/9,284= 7.7%

  22. Conclusion • The fact that the adjusted RR was different from the unadjusted RR is evidence that there is confounding. • Another symptom of confounding was identified by showing that there was an association both between bedsores and MS and dying and MS. • There was no association between bedsores and mortality.

  23. More….. • In our example, there is confounding by MS but does that mean that the association between bedsores and dying is not real? • If your answer is no, why do you say so?

  24. More….. • In our example, there is confounding by MS but does that mean that the association between bedsores and dying is not real? Answer: No. Patients with bedsores really do have a higher risk of dying but it is not because they have bedsores. Bedsores are guilty by association!

  25. Activity • Student handout

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