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UNCERTAINTY AT THE CENTRE OF SEPSIS

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Sepsis is a common and deadly condition, but diagnosis in not always knowable in real-time. The optimal treatment during times of diagnostic uncertainty differs across patients. Despite this reality, sepsis performance is uniformly assessed and reported for a population knowable only in retrospect—the patients ultimately judged to have sepsis at hospital discharge. This limits effective audit and feedback to incentivize clinician behavior. Personalized, real-time assessments of a patient’s risk of death and likelihood of infection could instead be used to guide treatment recommendation and performance assessment. Clinicians and health systems could be judged on whether their responses are appropriately calibrated given the urgency of the situation. Were antibiotics prescribed at an appropriate time given the urgency of the patient’s clinical status? With the information available, were the best treatment decisions made? Did treatment plans change as new data became available? Organizing treatment recommendations and performance assessment by risk of death and likelihood of infection could optimize sepsis care.

Publié dans : Santé
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UNCERTAINTY AT THE CENTRE OF SEPSIS

  1. 1. Hallie Prescott Uncertainty at the Center of Sepsis @HalliePrescott *This presentation does not represent views of US Government or Department of VeteransAffairs. Uncertainty at the Center of Sepsis
  2. 2. Take-home points • Guidelines & QI initiatives rigidly dichotomize • Benefit of early antibiotics varies • Diagnostic uncertainty is common • Why risk-based bedside management would be better
  3. 3. Seymour, et al. NEJM. 2017. Liu, et al. AJRCCM. 2017. Time to antibiotics in sepsis…. Alam, et al. Lancet Resp Med, 2018. “Vital” “Over- blown”
  4. 4. The effect of any treatment is highly variable across patients Riskof BadOutcome Sick Relative Risk Reduction Not sick Baseline risk Risk with treatment
  5. 5. The effect of any treatment is highly variable across patients Riskof BadOutcome Baseline Risk Relative Risk Reduction Risk of Treatment Itself Increasingly beneficialHarmful? No clear benefit Risk if Treated Early
  6. 6. Therapy Study 2:Study 1: SickNot sick SickNot sick
  7. 7. Study 2: NegativeStudy 1: Positive Average Treatment Effect in Study Population Seymour, et al. NEJM. 2017. Alam, et al. Lancet Resp Med, 2018. Therapy • 45% septic shock • 25% hospital mortality • 4% septic shock • 8% 28-day mortality
  8. 8. Does this patient have sepsis? On Vignettes Rhee, et al. Crit Care, 2016. Not Sepsis Sepsis YES NO Case 1 49% 51% Case 2 49% 51% Case 3 38% 62% Case 4 32% 38%
  9. 9. Does this patient have sepsis? On post-hoc review Klein Louwenberg, et al. Crit Care, 2015. 13% “No chance” 30% “Possible”
  10. 10. Guidelines & QI assume unambiguous diagnosis
  11. 11. Can we do better?
  12. 12. What does this mean? Density Time to first antibiotic
  13. 13. What does this mean? Density Time to first antibioticDensity Time to first antibiotic
  14. 14. What does this mean? Density Time to first antibioticDensity Time to first antibiotic
  15. 15. What does this mean? Density Time to first antibioticDensity Time to first antibiotic
  16. 16. Antibiotic timing similar across illness severity Liu, et al. AJRCCM. 2017.
  17. 17. But, is this possible? Risk-based guidelines work • anticoagulation for Afib • cholesterol targets • A1c targets Even blunt risk tools can help Spertus, et al. BMJ. 2015.
  18. 18. We should be asking: Given the situation: • was urgency of treatment appropriate? As the situation evolved: • was the treatment plan updated accordingly?
  19. 19. @HalliePrescott

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